HF SURFACE WAVE RADAR SIMULATION

J C Revel1 and D J Emery

ABSTRACT

One of the aims of radar performance modelling is to assess a radar’s capability to fulfil its intended mission. This may be achieved by the simulation of all aspects of the radar’s operation including target behaviour, environmental conditions, radar characteristics, and the radar/operator interface.

Various factors make the interpretation of a HF Radar display potentially more difficult than that of a conventional radar. First there is the large coverage area with potentially far more targets to monitor; second there is the slow update rate of a HF Radar due to the long integration times needed to achieve detection against clutter; and last there are the large variations in performance that can occur due to environmental factors.

To investigate these problems a comprehensive model has been developed whxh allows the exploration of the performance envelope over the whole range of possible environmental conditions. Databases of environmental, geographical and traffic data have been created which are used to generate full scale operational scenarios. These scenarios are fed through the performance model and a database of tracks is created which can then be played out in real time on a radar display. By this means the difficulties that an operator will face when trying to recognise targets of interest can be investigated and visual cues to aid his task can be developed.

INTRODUCTION

High Frequency Surface Wave Radars (HFSWR) exploit the surface wave mode of propagation to see low level targets beyond the conventional radar horizon. Generally this mode of propagation is only strong enough to be of use when the radiation is vertically polarised and propagating over a conductive surface such as the sea. Hence there has been considerable interest in recent years in the use of these radars for maritime surveillance especially as their range performance is comparable with the Economic Exclusion Zone limits that many nations are now imposing.

There are however a number of problems that need to be addressed before an operational HFSWR can be deployed. HF Radars are more sensitive to environmental conditions than microwave radars, the effect on performance from noise, sea state, and spectral occupancy can be considerable. Typical HT radar antenna arrays can be more than a kilometre in length which would make re-siting the radar very expensive. It is therefore essential to determine the radar’s performance in advance of choosing its site.

GEC-Marconi RDS Limited

4, 0 1998 The Institution of Electrical Engineers. Printed and published by the IEE, Savoy Place, London WC2R OBL, UK.

To achieve this goal we have developed a radar simulator which predicts performance using environmental data gathered from the potential radar site and traffic data from the proposed coverage area. The simulator generates tracks from this data which can then be fed into a radar display and played out in real time. Hence we can investigate how the radar will appear to the operator when it is deployed.

As well as allowing us to assess the suitability of potential radar sites the simulator provides a test bed for the development of the operator interface. The slow update rate of HF radars and the variability of the performance due to environmental conditions present us with a number of unique problems to tackle. The coverage area of a HFSWR is very large and we estimate that the amount of traffic that could be observed in a busy area will typically range from 200 to 400 tracks. With such a large number of tracks on display, all being updated very slowly (once every two minutes), the chances of an observer noticing an unusual event by casual observation is remote. He therefore will need a range of visual cues to aid him in his task. These may include guard boxes which define areas in the coverage which need special attention, velocity filters which allow the classification of targets according to their speed, and expert systems that can analyse the target's track and classify its behaviour (cruising, fishing, stationary etc.) The HF radar simulator gives us the opportunity to gauge these problems and to investigate their potential solutions.

User Defined Trafftc Traffic Database

Scenario Generator

Potential Tracks

Climate Database

Radar Tracking Model

Track Database

Electronic Environment

Figure 1 - Model Architecture

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MODEL ARCHITECTURE

The preparation and execution of the HF Radar Simulator is a four stage process. The first stage is the data gathering exercise to build the scenario database. Data is collected from a number of sources such as meteorological reports, air & sea traffic surveys, airline timetables, satellite data etc. Where data is unavailable (such as local noise conditions and spectral occupancy) a survey team is deployed to the site to gather data directly.

The second stage of the process is scenario generation, the gathered data is used to create all the potential target tracks that might be observed by the radar. The architecture of the scenario generator and the subsequent stages of the simulation are illustrated in Figure 1. The traffic database contains the data on all the potential targets that could appear in a typical day. It includes ports of origin, destinations, routes, and target sizes. To this data can be added a number of user defined tracks so that a more specific incident can be simulated such as an air-sea rescue mission, a pirate attack or a low-level air raid. The climate conditions which prevail during the scenario can be set as persistant or a climatic scenario can be defined by which means we may simulate a weather front moving through the coverage area.

The third stage of the process is to pass the potential tracks through a radar performance model. This model includes several databases; a climatic database which includes data on the prevailing wind & sea conditions; a clutter database which contains statistical data on clutter reflectivity; an electronic environment data base which includes details of atmospheric noise and spectral occupancy; and the radar parameter database which includes details on the HF Radar itself. The model calculates the probability of detection at all points along the track and then applies a tracking algorithm to these results. The tracks are then suitably formatted for input into our proprietary radar display.

The fourth stage of the simulation is to play the tracks on the real time radar display. This is based upon our proprietary radar display which has been modified to add rewind and fast forward functions.

SCENARIO DATABASE

The scenario database classifies targets into a number of categories such as scheduled airliners, local fishing, sea freight etc. For each category the database contains details on the ports of origin, destinations, routes etc. For some categories such as commercial airliners and ferries, this is in the form of time tables taken from published data, for others statistical data has been derived from traffic surveys (see [4], [ 5 ] , [6] , [7], & [SI for typical sources.)

A typical category is “Local Fishing Boats”. These are defined as boats that make daily trips to the fishing grounds, leaving port each morning and returning in the evening, hence their range from home port is limited. The data table for this category is a list of all the fishing ports within the radar coverage. For each port in the list the following parameters are defined:

0 the minimum & maxmum number of vessels that set out each day the minimum and maximum size of the fishing boats in terms of radar cross section (RCS)

0 a time window during which the fisihing vessels leave port a route to the fishing grounds

0 the area of the local fishing grounds a time window during which the fishing boats head back home

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From this data the scenario generator randomly creates a number of fishing boat tracks from each port starting at a randomly chosen time during the first time window. These tracks then follow the way points to a point in the fishing grounds where they then start moving in a pattern typical for a fishing boat. At a randomly chosen time during the second time window the boats start heading home.

RADAR TRACKING MODEL

The kernel of the radar tracking model is the HF surface wave radar equation. As given in [ 13 for any target of RCS CT the signal to noise ratio may be given by:

s - 4 .z . F . P , .ti .o . D , . D , 2

- AT c . N 0 . k .T . L , . L i

Here F is the operating frequency, P, the mean transmit power, ti the coherent integration time (CIT), D, the transmit antenna directivity, D, the receive antenna directivity, c the speed of light, k Boltzmann's constant, T the ambient temperature, No the external noise level relative to thermal noise, L, the system loss and Lb the one-way propagation loss (see [2]).

The equation is similar to the perhaps more familiar microwave version, but some of the terms have quite different characteristics. For example the propagation loss is smallest for high altitude targets (illuminated by the direct wave), greater for targets below the horizon but not on the sea surface, and then smaller again for targets on the surface (illuminated by the ground wave). Another important difference from microwave radars is that the noise term limiting target detection is of external origin (galactic, atmospheric and man-made noise) rather than being internal receiver noise.

Clutter retums must also be considered, and the most important of these are from the rough sea surface. Treating clutter as an unwanted target with RCS given by Aoo (where A is the area of the clutter and CT' the clutter cross-section density) the S/N equation may be used to calculate the clutter to noise ratio, C/N. Ionospheric clutter returns can also cause problems, though this is less simple to model.

Combining S/N and C/N to give S/(C+N) it is possible to determine if target detection will occur. Making multiple calls to this equation over a period of updates generates a sequence of target hits and misses. By applying a simple set of tracking rules to this sequence (e.g. at least 2 hits from 4 sequential attempts to initiate a track and 3 consecutive misses to delete a track) a track history for each target is created.

ENVIRONMENTAL DATABASES

A number of databases providing statistical information (either directly or indirectly) about several parameters in the radar equation are associated with the model.

Climate Database Using Global Wave Model data and recordings provided by the MET Office Marine Consultancy Service, a database has been developed giving wind speed and direction probability distributions by

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season for a number of geographical locations. These parameters influence sea state (and hence sea clutter and propagation loss) and also traffic profiles.

Sea Clutter Database The database has two sections, one giving theoretical clutter cross-section density spectra, and the other the statistical variation of the spectra. The first part was generated using a mathematical model at Marconi Research Centre and the second by using recordings from an experimental HFSWR. Sea clutter cross-section density varies with sea state, wind direction, operating frequency and Doppler.

C 0

0 al .- ... $10 0, L

I .- 0,

3 0 - -160

0 50 100 150 200 250 300 Doppler Bin

Figure 2 - Typical sea clutter cross section density spectrum.

Electronic Environment External noise levels have been characterised by the CCIR [3] for geographical location, season, time of day and frequency. Ow own recordings closely matched CCIR predictions, and also allowed a channel availability database to be generated to complement the CCIR noise database.

80

75 1

35 c 30

0 4 8 12 16 20 24 time of day

I

Figure 3 - Typical variation of external noise levels at 5 MHz (CCIR 322-3)

Y

TRACK DISPLAY

Figure 4 is a screen shot taken from a typical scenario. For clarity the traffic has been limited to local fishing boats and cargo vessels. Targets are represented by cross symbols, each target has a leading vector, the length of which is proportional to the target’s speed, and trailing dots depicting the track history. This scene is taken from the early hours of the morning, various fishing vessels can be seen heading out to the near shore fishing grounds. In addition there are a number of cargo vessels both inward bound and outward bound from a deep water port situated just to the east of the radar site.

.Figure 4 - Typical Radar Display

CONCLUSION

We have developed a useful model with a number of potential uses such as simulating HF radar performance in a real location prior to deployment and the test & development of HF Radar man- machine interface. If modified to produce tracks in real time it could be M e r developed into a full training simulator for HF radar operators.

Acknowledgements The authors wish to acknowledge permission given by GEC-Marconi RDS Limited to publish this paper.

REFERENCES 1. 2. 3.

4. 5 . 6. 7. 8.

Milsom, J.D., “HF Groundwave Radar Equations”, IEE Conf Pub. 441 , July 97, p285. ITU Geneva, “The Concept of Transmission Loss in Radio Links”, CCIR Rec 341-2, 1990 ITU Geneva, “Characteristics and Applications of Atmospheric Radio Noise Data”, CCIR Rep 322-3,1988 “Lufthansa InfoF 1 yway ”, http://www. lufthansa. com “Air Transport Action Group”, http://www.atag.org “The Mariner’s Handbook”, 6th Ed, The Hydrographer of the Navy, 1989. “Lloyds Ports of the World”, 1997 Sainsbury, J.C., “Commercial Fishing Methods”, Fishing News Books Ltd, 1986

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