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CSUN Autonomous Small Unmanned Aerial System for

Intelligence, Surveillance, and Reconnaissance

for

2012 AUVSI Seafarers Student Design Competition

Andres Chavez, Ben Hapipat, David Penniman, Hakim Bachmid, Hansolo Dela Cruz, Ivan Alvarez,

James Zimmerman, Jincun Wang, Joseph Saeed, Karam Kaoud, Maaz Waheed, Mustafa Qudsi, Nadine

Menjuga, Paulus Sunarli, Ruben Cuellar, Scott Schultz, and Ulysses Marquez

Department of Mechanical Engineering, California State University Northridge, Northridge California,

91330

Omar Flores, Pipat Jetawatana, and Ramzey Elallamy

Department of Computer & Electrical Engineering, California State University Northridge, Northridge

California, 91330

And

Dr. Tim Fox

Department of Mechanical Engineering, California State University Northridge, Northridge California,

91330

Abstract of Proposal:

The California State University Northridge (CSUN) Aeronautics entry into the 2012 AUVSI Seafarers

design competition is a Small Unmanned Aerial System (SUAS) consisting of a fixed wing Unmanned Aerial

Vehicle (UAV), a Payload, and a Ground Control Station (GCS). The system is capable of autonomous flight from

launch to recovery, able to conduct navigation through a multitude of waypoints while collecting images of the

ground below. Simultaneously an onboard computer processes each picture for potential targets then characterizes

each target for color, shape, orientation, as well as the co-located alphanumeric character and color. The user

interface for the UAV features flight planning software along with a graphical autopilot control. The payload

operator uses graphical interface for payload control and a self-populating spread sheet that is displayed to the user

allowing verification of the autonomous system. Additionally the system can connect to a Simulated Remote

Intelligence Center (SRIC) collecting a data file that can be downloaded by the operator.

California State University, Northridge AUVSI Page 2

Table of Contents 1. Introduction……………………………………………………………………………………… 3

1.1 CSUN Aeronautics Team…………………………………………………………… 3

1.2 Mission Requirements………………………………………………………………. 3

1.3 System Concept……………………………………………………………………… 4

1.4 Mission Preview…………………………………………………………………….. 4

2. Aircraft Design…………………………………………………………………………………… 4

2.1 Aircraft………………………………………………………………………………. 4

2.1.1 Airframe……………………………………………………………. 5

2.1.2 Launch and Recovery……………………………………………… 5

2.1.3 Propulsion…………………………………………………………. 5

2.1.4 Flight Control System……………………………………………… 5

2.1.5 Nose Video Camera……………………………………………….. 6

2.2 Navigation and Flight Planning ……………………………………………………… 6

3. Payload System…………………………………………………………………………………… 8

3.1 Imaging System………………………………………………………………………. 8

3.1.1 Camera……………………………………………………………. 9

3.1.2 Camera Interface………………………………………………….. 9

3.2 Camera Stabilization……………………………………………………….. 9

3.2.1 Gimbal…………………………………………………………….. 9

3.2.2 Gimbal Control……………………………………………………. 10

3.3 Target Recognition & Characterization………………………………………………. 11

3.4 Onboard Computer……………………………………………………………………. 14

3.5 SRIC Capability………………………………………………………………………. 15

4. Ground Control Station……………………………………………………………………………. 15

4.1 Pilot Operators Station………………………………………………………………… 16

4.2 Payload Operators Station…………………………………………………………….. 16

5. Communication…………………………………………………………………………………….. 17

5.1 UAV…………………………………………………………………………………… 17

5.2 Payload………………………………………………………………………………. 18

6. Safety……………………………………………………………………………………….. 18

7. System Validation…………………………………………………………………………………. 18

7.1 Aircraft and Airframe Components…………………………………………………… 18

7.2 Autopilot and Flight Planning………………………………………………………… 18

7.3 Imaging and Targeting………………………………………………………………... 19

7.4 Ground Control Station……………………………………………………………….. 19

7.5 Communication Test………………………………………………………………….. 19

7.6 SRIC………………………………………………………………………………….. 19

7.7 Checklist……………………………………………………………………………… 20

7.8 Full System Test……………………………………………………………………… 20

7.9 Safety…………………………………………………………………………………. 20

8. Conclusion………………………………………………………………………………………… 20

9. Acknowledgements………………………………………………………………………………. 20


1. Introduction

CSUN Aeronautics has designed and developed many mission specific unmanned aircraft for

multiple collegiate competitions. The design for the UAS System was based on previous experiences

from SUAS competitions where a reliable yet limited lifetime UAV was designed and paired with a

payload system to meet multiple mission specific requirements. Specifically the UAS developed for this

competition can be easily transported, quickly assembled, operated with a minimal crew, while providing

a robust and mature ISR system.

1.1 CSUN Aeronautics Team & Design Method

CSUN Aeronautics consists of students from multiple engineering disciplines such as Computer

Science, Aerospace, Mechanical, Civil, Electrical and Computer Engineering attending CSUN. The

current team was formed throughout the summer of 2011.

The team used a systematic approach to the design of the UAS starting with a preliminary

analysis of the mission concept defined by AUVSI. Requirements and objectives documents based on the

KPP’s for the various systems, subsystems, and components were then completed and a preliminary

design was developed. A PDR was held as exit criteria from the definition phase of our project before

entering the design phase. In December a CDR was held to verify that the design met the requirements

established. Once the design was approved, the development phase began with fabrication and

integration. Attendance at the AUVSI Seafarers competition defines our operational phase.

1.2 Mission Requirements & Goal Statement

AUVSI’s mission concept required the design an UAS that was a reliable and robust system

capable of accurate ISR while utilizing both system autonomy and human interaction when practical. The

mission timeline provides a 40 minute set up window prior to launch, following which, autonomous flight

through a waypoint series while acquiring targets both on and off the UAV flight path, searching a

predetermined area for potential targets, and acquiring data from an SRIC are planned. Additional points

are also awarded for autonomous takeoff and landing, as well as actionable intelligence, in flight re-

tasking, autonomous target characterization, and gathering data from an SRIC.

The team’s goal was to design and create a mature and robust small unmanned aerial system that

meets the AUVSI key performance parameters while being a user friendly and innovative design.

Fig. 1 Illustrated Mission Requirements


1.3 System Concept

The UAS developed consists of three main components, a UAV, Payload, and Ground Control

Station, along with operations manuals and checklists for each component.

The UAV is a hybrid canard configuration with forward horizontal tail providing increased

endurance and aft vertical tails providing yaw stability. To optimize system performance the design of the

UAV was accomplished in house providing greater payload flexibility.

The payload is an independent system contained in the UAV utilizing only the aircraft fuselage as

containment. To minimize future ground control station size and complexity as well as decrease required

communication bandwidth image processing is accomplished within the UAV. The camera is mounted

on a single axis gimbal acting about the aircraft’s longitudinal axis increasing system reliability.

The Ground Control Station was designed to be operated by two crew personnel consisting of a

pilot responsible for operation of the UAV as well as system safety, and a payload operator responsible

for the operation of the payload and mission planning. The pilot interfaces with the aircraft and autopilot

through a program called virtual cockpit that supplies the operator with real time flight data including a

map overlay and artificial horizon. Communication to the payload is done through a CSUN developed

payload control that features a camera and gimbal control as well as a real time potential target

spreadsheet.

1.4 Mission Preview

Within 40 minutes of arriving to the designated mission sight the aircraft should be capable of

beginning the mission. Preflight and safety briefings may take place during this time frame. After the 40

minute set up time, the aircraft will takeoff, fly autonomously through the assigned waypoints, stay within

the assigned airspace, enter an assigned search area at an altitude between 100 and 750 feet MSL, image

and characterize potential targets, land the aircraft autonomously, and deliver image data to the judges.

During the mission the UAS may also be re-tasked to do perform a search of a new location and to collect

data from an SRIC. The mission is to be completed between a time frame of 20 and 40 minutes.

2. Aircraft Design and Overview

2.1 Aircraft

The FF12 aircraft was designed and constructed primarily by CSUN Aeronautics specifically for

the mission and payload requirements. A design load of +5 and -3 G’s was utilized for flight load

conditions and a safety factor of 2.5 was used for all design limits. Additionally the airframe was

designed to be quickly and easily constructed as well as repaired. An emphasis on low parts count and

interchangeable parts resulted in a very simple and light weight UAV weighing 16.4 pounds with an

overall length of 98 inches.

Fig. 2 The Flying Fox 2012 showing payload access


2.1.1 Airframe

The fuselage features a monocoque shell design composed of a fiberglass/epoxy laminate with

strategically placed wood formers that transfer load into the skin from various components. The fuselage

utilizes a removable top access hatch that is secured with Velcro allowing quick and easy access to the

payload and avionics. Construction was accomplished using three female molds fabricated in house

allowing multiple parts to be built for mockup and development.

Foam core, laminate sandwich construction was used for the wings, canard, and tail of the

aircraft. This method used an outsourced CNC cut foam core that was laminated with a fiberglass/epoxy

skin resulting in a simple and light weight structure. In house construction provided the ability to iterate

designs, as well as construct replacement and spare parts as needed. An 80 inch span wing is constructed

in two halves that join together with a 1 inch carbon fiber tube. The wings are locked onto the aircraft

with two metal pins that have large red caps, allowing easy assembly verification.

A 40 inch span canard made of 1.5lb density foam with a fiberglass/epoxy skin mounts to the

front bottom of the fuselage with one ¼ inch nylon bolt designed to break prior to aircraft structural

damage.

Behind the aircraft, the vertical stabilizers and rudders mount to the wing using removable rigid

carbon tubes and are interchangeable left to right. The vertical stabilizers are made with 1lb density foam

skinned in fiberglass/epoxy laminate. They are joined to the aircraft using four red nylon bolts visible to

the ground crew for assembly verification. The tails lower portion of the tail is designed to impact the

ground before the propeller at high pitch angles. Located 20 inches apart on either side of the propeller

the tail booms also act as a safety barrier to the propeller.

2.1.2 Launch and Recover (Landing Gear)

Early in the design process it was decided that a rolling takeoff and landing was most appropriate

for our system, both for development and operation. Although a catapult launch and belly landing can be

accomplished with this system, the competition aircraft uses a tricycle type landing gear with fixed rear

main gear and a retractable steerable nose gear. Landing gear parts are standard COTS hobby type.

2.1.3 Propulsion

Aircraft propulsion is all electric and provided by an AXI 4120/20 motor with a 17x8 propeller

capable of 9 lb. static thrust. The system uses two 22.2V lithium polymer batteries with 2100 mA-hours

for the onboard computer and 8000 mA-hours for the motor and capable of providing the UAV with 50

minutes of endurance and nominal cruise conditions.

2.1.4 Flight Control System

Aircraft flight control consists of a standard aircraft layout of elevator for pitch, aileron for roll,

and rudder for yaw. Each axis uses two separate surfaces with independent servo drives which reduce

single point of failure items. All flight controls are constructed from balsa wood covered in lightweight

Monokote film and attached to the aircraft using a hinge tape. Flight control servos are located as close as

practical to the flight control surface and are accessible without the need to remove access panels

allowing easier adjustment.

The flight control system is primarily controlled by a Procerus Kestrel autopilot that was

primarily selected based on CSUN’s experience with the system and availability. With this system aircraft

speed and altitude are determined through the use of a nose mounted pitot tube that allows the autopilot to

receive outside static and dynamic pressure. Aircraft orientation is determined by using a 3 axis inertial

measurement unit (IMU) that is contained within the autopilot itself. Location is determined using a GPS

receiver that is connected directly to the autopilot.


Flight control protocol requires the safety pilot to give control of the UAV to the ground control

station before any autonomous commands can be executed. Control is transferred from R/C to Autopilot

through a Pololu multiplexer board that connects either the RC receiver or autopilot to the flight control

servos. The multiplexer board is set to default to the RC control if power or control is lost. The autopilot

uses an additional expansion board to allow control of nose gear steering as applicable to takeoff and

landing as well as allow the pilot to retract the nose gear from the ground control station.

Fig 3. Flight control system design

2.1.5 Nose Video Camera

CSUN developed a requirement to provide the pilot and payload operator a view from the aircraft

as if they were onboard. The nose video camera system was designed to provide the operators with a real

time feel to the mission increasing system awareness and providing a system that could preview the

upcoming terrain to the payload operator. The nose camera is mounted in rapid prototyped mount and

angled 15° downward.

2.2 Navigation & Flight Planning

Aircraft navigation is performed by the Kestrel autopilot which guides the aircraft through a

series of waypoints that are defined in three dimensions. Each waypoint has a sphere around it, that when

the UAV enters the sphere it will consider it as met the waypoint objective and proceed to the next way

point. The aircraft may also be commanded to hold at a location which results in the aircraft flying

leaving its flight plan and orbiting a location until told to return to its flight plan or begin a new task.

For all flights a series of way points must be generated that will compose the flight plan, during

the competition the waypoint navigation series is provided to us. However for the search areas a flight

plan must be created. For this a VBA macro file is used in conjunction with Excel. The search area

boundaries are inputted using lat/long coordinates and the macro will generate a flight path through the

search area. The flight plan is then saved ready to be loaded with Virtual Cockpit and ultimately

uploaded to the autopilot.


Fig. 4 Training flight plan showing operator interface

Fig. 5 Internal layout of UAV fuselage

The UAV was designed to meet the AUVSI objectives of an autonomous platform that could position

the payload over a desired imaging location. Additional design decisions were made allowing autonomy

which has safety and mission assurance benefits such as flight control autonomy from takeoff to

touchdown which provides a more predictable flight path over an RC pilot. Human interaction was

included where safety and mission assurance required it such as re-tasking, flight plan development, and

verification.

3. Payload

The AUVSI KPP’s, should, and shall statements generated payload design requirements that were

developed into component requirements for an imaging system , an image stabilizing system, a target

detection and characterization system, an SRIC system, all of which interface with or are contained in the

onboard computer.

The SP12 Payload is a stand-alone system with a self-contained power and sensor sources allowing

independent operation from the UAV. The payload imaging and stabilization system uses Canon


Powershot A620 camera that is located within a single axis gimbal system that allows acquisition of off

axis targets and minimizes flight disturbances. This connects to a PCM computer with an Intel dual core

processor that runs the target detection and characterization system. The CSUN developed software is

used to autonomously locate potential targets, crop around a possible target, and then characterize the

target. The computer is also able to perform SRIC tasks using separate Wi-Fi network is carried aboard

allowing independent data links.

3.1 Imaging System

To satisfy the payload requirement to gather images of the terrain designated as a search area an

imaging system was designed to gather photos of the area specified by the payload operator. The imaging

system consists of a camera and associated software required to control it.

3.1.1 Camera

For the competition the AUVSI requirements and CSUN flight strategy required the system have

the capability to recognize a target off axis (i.e. 250ft off flight path) at an altitude of 200ft AGL and to

recognize an en-route target at an altitude of 500ft AGL. Based on the imaging software developed it was

determined that it would be necessary for each image to maintain a ratio of at least 12 pixels/foot. An

additional requirement was that the image transfer rate from the camera to the on-board computer be

2s/image at max.

A Canon A620 Powershot camera was chosen for simplicity and ease of interface software

programming and availability of development kits to altering of the camera’s software controls. The A620

also had significant weight and cost advantages over a larger DSLR type camera. The Canon A620 has a

7.1MP CCD which suffices for the amount of pixels needed for the imaging payload.

Fig. 7 Canon A620 Powershot

3.1.2 Camera Interface

The software used is a beta program called SDMcon, currently being developed by a freelance

programmer in the United Kingdom. The program allows for a user to remotely access the camera from a

computer through the use of a USB connection. From the computer the user has access to various camera

functions such as zoom, ISO setting, and shutter speed. This is made more readily accessible through a


developmental GUI, also still in the beta phase. The current programmable capabilities of the program

include the ability for the camera to be set-up and “left alone” to perform a set of functions. This includes

being able to take a user-specified amount of pictures, and subsequently upload them with the simple

push of a button.

These various capabilities of the camera allows for the project to accomplish the task of capturing

object images during flight through the use of autonomy. Essentially, the camera could be tasked with a

set of functions and left to perform them throughout the course of the flight. During the course of the

mission, the camera will be set-up to take a batch of images, dependent on how many is needed for the

section of interest, and corresponding parameters will be adjusted in terms of camera settings. From there,

the camera will automatically upload those images, reset and be ready for the next batch to begin.

3.2 Camera Stabilization

Controlling the orientation of the camera was vital to the CSUN Aeronautics flight strategy. The

UAV was determined to be most variable about the longitudinal axis during flight, and with additional off

axis targets now placed in the waypoint navigation sequence, our design requirements determined a single

axis gimbal should be included. To meet these requirements a stabilization system that would actively

control the camera about the longitudinal axis was designed. The stabilization system has two main

components, a gimbal system allowing rotation about the aircraft roll axis, and a controller that reads

orientation from a 3DOF IMU and converts it to a servo drive command controlling a Parallax continuous

rotation servo that is gear coupled to the gimbal.

Fig. 8 Canon A620 and Gimbal

3.2.1 Gimbal

As the entire system was iterated, optimum camera placement was determined to be within the

fuselage with a hole or slot for the camera field of view. The gimbal components were constructed on a

rapid prototype machine, which printed plastic gimbal components using a material similar in property to

ABS Plastic. This process resulted in quick manufacturing and low parts count. The gimbal uses 4 main

components, a frame that is bonded to the fuselage during manufacture, two removable bulkheads, a

camera frame with integral gear, and a servo mount.

While imagine the aircraft roll rate was determined to be below 100°/second therefore the gear

ratio was determined to be 3:1 using the Parallax servo. The camera gear was designed as an integral part

of the camera frame while the servo gear was designed to fit over an existing servo head reducing


manufacturing needs. The system has a travel arc of 180° which mitigates an off line condition, while

neither gear contain travel stops ensuring that if an offline condition is reached the gimbal will not bind.

Multiple fasteners are imbedded into the plastic components reducing both maintenance

requirements and the risk of foreign object damage. The gimbal is removed from the aircraft by removing

either the front or rear bulkhead which frees the camera frame from the aircraft. The gimbal system is

modular, compact, and easily iterated for camera updates.

3.2.2 Gimbal Control

To manipulate the gimbal, a control system was required that could position the camera at a

relative to a vertical as determined by the payload operator. The control architecture of the image

stabilization system was given the name S-Chain and designed to exist separately while supporting the

imaging system within the payload. The S-chains primary task would be to hold the camera stable

relative to a vertical plane coincident with the longitudinal axis of the plane, the relative angle would

nominally be 0° while performing most tasks, however can be manipulated by the payload operator up to

50° when off axis targets acquisition is desired.

The control system is based off orientation feedback from a 9DOF Razor IMU’s ATMega328

microcontroller’s boot loader which runs a script controlling a continuous rotation Parallax servo. The

IMU is mounted directly to the camera housing with foam tape to reduce vibration feedback. The

microcontroller is powered by USB from the on-board computer system. The control script uses a

proportional control where rotational speed is based on the difference in the desired and actual roll angle.

Along with being able to control the rotation, we have to ability to lock the gimbal in place if need be.

Fig. 9 Control Architecture of Camera Stabilization System

This system met our design requirements by holding the camera stable about the roll axis during

roll rates predicted to be seen during ISR flight.


3.3 Target Recognition & Characterization

Vital to our autonomous ISR design goal, a target recognition system was required that could

identify potential targets contained in the images provided by the camera. This system was integral in the

system meeting the AUVSI KPP’s related to target recognition.

Our entry to this year’s AUVSI competition will includes a prototype software program called the

Malinoski program that performs autonomous object detection and recognition using Open Computer

Vision (OpenCV). OpenCV is an open source computer vision library originally developed by Intel

using libraries written in C/C++ and has the ability to interface with Python. Unlike other proprietary

systems like Matlab and Labview, OpenCV does not need a runtime engine and can be incorporated into

existing code.

The object detection and recognition process examines all input imagery for potential targets and

their characteristics. Images received from the camera undergo a contrast threshold for edge detection.

The source image, in an RGB format, is split into the individual color channels. Each channel is evaluated

at 3 different levels (64, 128, and 192 respectively). Each channel subsequently becomes a binary image.

Pixels are grouped with neighbors to make consecutive surfaces. This process is performed in hopes of

separating the target with the background. Targets that meet the surface area range for legal sizes are kept

for further examination. The figure shows this process being performed on an image.

Fig. 10 Filtering Process of Retrieved Image

The next phase examines potential targets that meet a polygon description. Edges in the binary

images are represented by a contour object. A contour in this context is a collection of two dimensional

points. Points in the collection are stored linearly where points immediately before and after any given

point is a direct neighbor. Because these contours have potential information about a shape, each is

evaluated for geometrical properties. Contours are matched against a list of shape descriptors: convexity,

the number of vertices, the length of edges, the relationship between edges, and the angles at each vertex.


The figure below shows that a triangle and the outline of the Latin character ‘A’ are what remain of this

process. Previous edges that failed to meet a polygon description are discarded.

Fig. 11 Target being evaluated for Outlines and Characters

Edges that meet the polygon descriptors are kept for the next process: color recognition. The

edges that describe the shape are used to crop the target from the original image. Pixels that fall within the

edge boundaries are considered target surface area. These pixels are used as input to a k-means clustering

algorithm. K-means is an unsupervised clustering algorithm that partitions a data set into k different

subsets. Each target is to have only two colors: a surface color and an alphanumeric painting. These

colors should create two natural looking groups in 3D space. By setting the partition to k = 2 groups,

group ‘centers’ are found. These centers represent the average value per partition, which consequently are

the colors of the target and alphanumeric character. Each center is matched against a list of predefined

colors using Euclidean distance. The closest values are tagged with color names.

Fig. 12 Process of Identifying Target & Training Examples

The target has now been identified for a shape, the shape color, and the alphanumeric color. The

process now continues to alphanumeric character recognition and orientation. Early prototypes for

character recognition utilized neural networks for identification. This artificial intelligence proved useful

with the caveat that it only worked on single orientation characters. Large distortions in rotation rendered

the character unrecognizable. The solution to this problem was to use support vector machines (SVM).

This concept works by dividing spatial data into different categories. Each target is pushed through

another threshold level. This is done to separate the character from the background. This new binary

image is used as input to an SVM. The SVM uses this spatial data to identify not only the character but

the orientation that it resides in.


Fig. 13 Spatial Data for Identification & Character Orientation

The SVM required several thousand training images using fonts that could potentially represent

the alphanumeric character. After carefully examining fonts made available through commercial word

processors and those available on the Internet, a total of 8 fonts were used for training. Each font was

recorded for the Latin alphabet and numbers 0 through 9. For each character, the training process

randomly selected a font, rotated the character to a cardinal direction, and slightly warped the perspective.

The different fonts were used to compensate for the variability in the potential look to characters. The

rotations were necessary to be able to recognize the target in different configurations. Perspective warps

were added to include a window of noise or randomness to the image. It is known that images will not be

taken at a perfectly flat angle and that distortions will arise. The figures below show the fonts used for

training and some sample training data.

Targets have now been identified with a shape descriptor, a color, an alphanumeric character, the

alphanumeric character color, and an orientation. All characteristics are then packaged into an XML file

for transmission. This XML file and a cropped target from the image are transferred to the ground station

via the FTP protocol. Communication with the UAV and the ground station is facilitated use the cURL

software library. It is freely available, is written in C, and abstracts out a lot of the complexities involved

with network communication. Both files are transmitted to a file server on the ground station.

One of the ground station computers will have FileZilla and Microsoft Excel installed. FileZilla

receives target transmission data from the UAV. All data received is placed into a directory where an

automated script will extract target details and import them into an Excel workbook. The workbook is

used to present real time and updated target data to the judges. The workbook can be printed at any stage.


Fig. 14 Spreadsheet generated for Payload Operator

3.4 Onboard Computer

Our payload design required that the images taken by the camera, be processed to identify

possible targets, and characterized to determine target characteristics. This could either be accomplished

at the ground control station or within the UAV. With increasing autonomy desired, the program

designed to accomplish this required little human interaction therefor containing the image processing

within the UAV was a logical choice. The ability to accomplish the target recognition and

characterization within the UAV increases system flexibility, reduces bandwidth requirements, and in a

defense environment increases security. While the images can be processed for target identification and

characterization on board the aircraft, the ground control station is equipped with duplicate software

allowing ground and or post flight processing if needed.

To sufficiently run the target identification and characterization program discussed earlier, a

1GHz processor speed compatible with Linux or Windows, and at least an 8GB hard drive was required

to store the operating system and data. The on-board computer selected was the PCM-9363, which

features a 1.8GHz dual core Intel processor, and 4GB of RAM running Windows 7. The hard drive picked

to match this computer was a 32GB Patriot Torqx 2 solid state drive and is used to meet the memory

requirements and provide system modularity. The computer is responsible for controlling and triggering

image capture and geotagging data, processing images using the Malinoski program, and executing data

transfer to the GCS. When an imaging sequence is desired, the payload operator will send a batch amount

and a start command to the onboard computer which will then trigger the camera to begin imaging until

the batch amount is accomplished. As the images are being taken, the camera’s autofocus light triggers a

photodiode which synchronously captures the geotagging information (GPS, IMU, and magnetometer

readings) and saves it in an XML file. When the batch is complete, the computer will then download the

images from the camera and store them to be processed when available.

Processing is accomplished using the Malinoski program which copies files from the queue folder

and characterizes them for potential targets as previously discussed. The positive files are then sent to a

target folder where they are correlated with their respective data file containing camera orientation,

altitude, and position. Once correlated the files are transmitted to the GCS via the primary Wi-Fi network

for operator in the loop review. All files are stored in the onboard hard drive if needed for further review

or communication failure.


Fig. 15 Image transfer architecture

This selection of components met the basic design requirements by processing the images within

the UAV allowing future decreased ground control station requirements.

3.5 SRIC Capability

The payload is also required to carry an SRIC capability. This is accomplished by entering the

provided information for the SRIC Wi-Fi network to the network configuration of Windows 7 used in the

onboard computer. When within the vicinity of the SRIC location, the operating system will allow a

secondary Wi-Fi adapter to connect to the SRIC Wi-Fi network automatically, and allow the payload

operator to search for the file with the given file path via Remote Desktop.

4. Ground Station

With a focus on increasing UAS autonomy the ground control station requirements and duties should

decrease, however relying on an over autonomous system generates a higher level of risk in development.

To mitigate this risk the ground station was required to provide both the pilot and payload operator

enough information that he or she would be able to manually regain control of the system and safely

complete or terminate the mission. This is done on the pilot side through the use of a backup RC pilot and

assisted with a forward looking camera and HUD. On the payload operators side this is accomplished by

providing duplicate software available in the plane to the operator on the ground as well as storing all raw

data that the payload operator can access either by virtual desktop or through a LAN network post flight.


Figure 16: Ground control station design

4.1 Pilot Operator Station

Control of the UAV is essential to mission execution and safety, for this a reliable and user

friendly interface with the UAV is required. The pilots station is based around a program called Virtual

Cockpit which allows the user to interface with the UAV in a method that mimics and actual aircraft

cockpit. It provides the user real time UAV data via a primary flight display including an artificial

horizon with flight data overlay and a ground map of the desired area with a graphical representation of

the flight plan and current aircraft position. The flight plan overlaid on the ground map also highlights

the waypoint that it is currently navigating to providing the operator feedback of the UAV’s intended

course.

Virtual cockpit also allows the user to communicate with the aircraft through a flight plan either

by visually entering waypoints on the map which would be applicable during a hold task, or by pasting in

lat/long coordinates as discussed in the flight planning section, applicable for a complex area search task.

Aircraft control is further enhanced by a suite of features such as a hold around a point, return home, and

land that the pilot may choose to select depending on mission requirements.

Virtual cockpit also provides its own flight plan verification system where the user can simulate a

flight plan based on the aircraft performance and current weather conditions after which the user can

iterate a flight plan ensuring the aircraft will travel over the intended path.

The Pilots station is further enhanced by displaying the nose video camera feed directly to the

pilot. This combined with a data overlay provided by the autopilot system provides a true heads up

display. The nose video camera is mainly cursory feature however it was vital to the development

process and determined to give the pilot a real time feel to the mission.

4.2 Payload Operator Station

While the pilot’s station ensures the payload will be placed over the intended locations, it is the

payload operator who must ensure the proper data is gathered. To accomplish this task the payload


operator is required to set up and monitor the imaging system, ensure proper camera positioning, and

monitor target acquisition and characterization.

The systems primary task is to collect images of ground targets along with their characteristics

and location. This data leaves the UAV and travels to the ground station in a variety of formats. The

pictures are sent as .jpg files that are time stamped from the camera as well as the corresponding .xml that

uses a time stamp as a title and contains the corresponding GPS, IMU, and magnetometer data. The

ground station algorithm collects these files determines the image location using the data in the .xml file,

then uploads that into a spread sheet with the corresponding .jpg image of the target for the operator to

review.

To support the imaging task, the payload is equipped with a gimbal that can be commanded to

hold an angle relative to vertical. To meet the off axis target requirement, the payload operator station is

equipped with a gimbal control that allows the user to input the desired relative angle relative to vertical

that the gimbal should hold.

As a secondary task the payload is designed to access an SRIC, to accomplish this, the payload

operator is provided with an interface allowing the input of a WEP key and pass-code. When SRIC

operations are desired the user simply triggers the task and can view the files as they are downloaded.

5. Communication

Constant contact with both the UAV and payload is required for a successful mission, to

accomplish this, the ground control station is equipped an antenna array communicating both with the

UAV and GPS. The UAV features a communication protocol where failures trigger a communication

handoff to another system while the payload uses single source links where interruptions are handled by

re-sending data. Both systems handle abnormalities differently providing both safety and mission

assurance.

5.1 UAV

Primary flight control of the UAV is accomplished through a 900MHz radio modem that connects

the Kestrel autopilot to the pilot and virtual cockpit within the GCS. This is accomplished with a dipole

flat patch antenna located on the UAV belly and a Commbox with self-contained power supply located at

the ground control station. The Commbox is then connected to a laptop via an RS232 port and a primary

RC transmitter used by the backup pilot.

Secondary flight control is accomplished through a 2.4GHz RC transmitter communicating its

respective receiver within the UAV. This transmitter is also manned by the safety pilot and is used if the

900MHz link is lost. This link is also used to both arm, by giving control to the ground control station

pilot, or disarm, by removing the ground control station from the loop.

Tertiary communications are accomplished through the downlink of the live nose video feed via a

1.3GHz link using a transmitter in the aircraft and a dipole antenna on the ground. The nose video

receiver requires is an omnidirectional antenna.


Position data is supplied to the auto pilot via GPS through a uBlox GPS receiver mounted on a

ground plane and located under the fiberglass upper skin of the fuselage. A second receiver is connected

to the Commbox and provides differential GPS to the system reducing position error.

5.2 Payload

Payload communication is accomplished through two Wi-Fi networks operating on 2.4GHz. The

primary network is used to connect the ground control system with the onboard computer and consists of

an Alfa 2.4GHz USB wireless antenna onboard the aircraft and an ultra-long range directional Wi-Fi

adapter at the ground control station. The ground control station requires it to be pointed at the UAV

within a 14° cone and is manually positioned.

The secondary network uses an identical Alfa antenna also connected to the onboard computer

but is used for identification and connection to the SRIC.

To determine target location the Arduino microcontroller is triggered to write the GPS data

collected from an Eagle Tree GPS antenna to an xml file when a picture is taken. The Eagle Tree antenna

is located under the upper skin of the fuselage.

6. Safety

System safety and mission assurance is accomplished through design and practice. Design

choices were made to promote safety such as having tail booms acting as a propeller barrier, and a

redundant flight control system both in the air and on the ground. Safety and mission assurance is

practice during operation through training, team briefings, assigned duties, and the use of iterated

checklists.

7. System Validation

Validation of the FF12 UAS system was accomplished using both analysis and testing on individual

subsystems and full system when applicable.

7.1 Aircraft & Airframe Components

The aircraft design was validated using x-plane simulation software that allowed performance

models to be validated prior to flight. The design was then further validated using the kestrel autopilot

data logging feature to record flight data for post flight analysis. Airframe structure was validated using

both FEA and coupon testing. Coupon testing was performed on representative structures while solid

modeling and FEA were used to verify component interaction. The aircraft design and structure were

further validated during a 15 individual test flight designed to validate that aircraft design and identify

operational parameters.

7.2 Autopilot & Flight Planning

Validation of the autopilot comes from working a flight simulator called Aviones. The model of CSUN’s

UAV is constructed with accurate parameters and performance. Lift, center of gravity, moments, wing

loading all were considered into the construction of the model in Aviones. Model simulator tested the

performance of the aircraft to verify the calculations are accurate and performing the as expected. The


Aviones model was imported to Virtual Cockpit where a simulation of the UAV can be run. In the

simulation inside virtual cockpit, the aircraft can be seen whether or not it can handle all the given

waypoints uploaded to the aircraft. Virtual Cockpit makes its calculations based on the Aviones model.

To adjust for incomplete data or missing parameters in the simulation the stability of the aircraft can be

perfected even further with the use of PID controls through virtual cockpit.

7.3 Imaging & Targeting

Payload verification was accomplished using task scenarios on both individual subsystems, and

the complete payload system. A full system bench test was performed, prior to installation in the aircraft.

The targeting sub system was verified after many training scenarios where the system learned

multiple fonts and colors. The verification of the targeting system resulted in a 79% success rate.

7.4 Ground Control Station

Ground Control Station verification was performed in conjunction with correlated systems. The

pilot station was verified in conjunction with the aircraft navigation system through the use of Aviones

software which was able to mimic aircraft performance through simulated flights. The payload operator

station was verified through individual component and full system tests on the payload. Additionally the

payload ground umbilical system was verified through testing.

7.5 Communication

Communication systems were verified individually and as a complete system through ground

range testing prior to flight. The following table lists the demonstrated ranges of each of the

communication links.

Table 1 System range testing

Apollo Field Van Nuys, Ca

Network Frequency Range Tested Successful

Autopilot 900 MHz 3000 ft Y

Nose Cam 1.3 GHz 3000 ft Y

R/C 2.4GHz 3000 ft Y

Porter Ranch, CA

Computer Wi-Fi 2.4GHz 3000 ft Y

The control priority discussed in the flight control section was verified to show that at any time

the RC pilot can take control of the aircraft using the 2.4GHz transmitter.

7.6 SRIC

The SRIC connectivity protocol was tested in lab conditions, while the full SRIC system

including aircraft orbit will be tested during the payload verification test flights.


7.7 Checklist

Checklist verification was and is currently accomplished during fight test and training scenarios.

7.8 Full System Test

A full UAS system with payload is projected to be flown on June 1st and will be verified using

multiple flight plan scenarios to accomplish takeoff, waypoint navigation, area search, SRIC acquisition,

and landing. During this simulation real targets will be used to establish full system target reliability.

8. Conclusion

Based on the requirements and goals for this year’s UAV, a complete system was successfully design

and built through a systematic approach evaluating all aspects of autonomy, safety and overall mission.

This paper was able to show this process and how it was implemented throughout design, manufacturing,

testing of this complete UAV system. Furthermore, to ensure a successful mission a significant amount

of hours were specifically design for testing. Having met all of the requirements, the Flying Fox 12 team

is overwhelmingly confident that a successful mission accomplishment will be met and looks forward to

this year’s AUVSI student competition.

9. Acknowledgements

The CSUN Aeronautics team wishes to thank our advisor, Professor Tim Fox to whom the

aircraft is named after. Our graduate advisors, Ammy Cardona (USAF), Anton Bouckaert (Boeing-

SpectroLab), Franz Revalo (USAF-CIV), Hooman Fatinajed, Jack Carrick (L-3 Communications), Mahdi

Ghalami, Phillip Malinoski (HAAS), Ryan Schaafsma, and Tomasz Dykier.

We would also like to acknowledge the financial contributions from the CSUN Department of

Mechanical Engineering, CSUN Associated Students, Astro Aluminum Inc., Dickson Testing Company

Inc., and Aerocraft Heat Treating.

Additionally the team has been honored to have the help of student engineer volunteers, Curtis

Darby, Sandy Otero, and Thad Moody who have been invaluable to the team and are excited to lead next

year’s team to success.

Fig. 17 UAV climbing during test flight

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