Large Format, Fast, 0.5erms CIS with Oversampled … · SUB‐ELECTRONLOW‐NOISECMOS IMAGE SENSORS Large Format, Fast, 0.5erms CIS with ... TWO-STAGE ADCFORLOW-NOISECIS

SUB‐ELECTRON LOW‐NOISE CMOS IMAGESENSORS

Large Format, Fast, 0.5erms CIS with Oversampled 2‐Stage ADCs

J. A. SEGOVIA, F. MEDEIRO, A. GONZÁLEZ, A. VILLEGAS

TELEDYNE ANAFOCUS

and

A. RODRÍGUEZ-VÁZQUEZ

UNIVERSIDAD DE SEVILLA, IMSE/ [email protected]; [email protected]

Research of Angel Rodríguez-Vázquez supported by the SMART CIS3D, Junta de Andalucía P12-TIC-2338 Project

THE INVISIBLE IMAGER FLOOD

NOISE IN IMAGERS

TEMPORAL PIXEL NOISE

TWO-STAGE ADC FOR LOW-NOISE CIS

CHIP-LEVEL NOISE REDUCTION

FINAL REMARKS


NOISE IN IMAGERS




FINAL REMARKS

S4EVOLUTION OF IMAGE SENSORS MARKET

Source : Yole Development, 2016. www.yole.fr

RAPIDLY GROWING MARKET

S5. . . INVOLVING MANY CONCURRENT TECHNOLOGIES


S6

Source : R. Fontaine, The State of the Art of Mainstream CMOS Image Sensors, Int. Image Sensor Workshop, 2015

EVOLUTION OF IMAGE SENSORS IP

HIGHLY INNOVATIVE MARKET

Active Image Sensor Patent by Year of Issue (1994-2014)

(based on Chipworks´ search methodology; favors fabrication patents

Year of Issue (or laid open)

Pub

licat

ion

Cou

nt

S7. . . IMAGERS ARE FLOODING OUR TERRITORIES

One image is worth more than thousand words:

Two Snapshots of Via Della Conciliazione, with eight year time interval:

Source : Der Spiegel

Exponential increase of the usage in consumer applications

S8. . . AND FLOODING IS NOT LIMITED TO CONSUMER APPS


S9INCREASING VOLUMES IN EMERGING AREAS

Source: IC Insights

S10

Source: QUALCOMM, “Emerging Vision Technologies: Enabling a New Era of Intelligent Devices”, TR 2016

ARTIFICIAL VISION: A DISRUPTIVE TECHNOLOGY

S11

UBIQUITOUSELECTRONICS AND

INFOTECH

Personal

Entertainment Transportation

SurveillanceEnvironmental

Energy/Smart Grids

Internet of Things

Health

Brain-Machine

Interfacing

Etc. . .

… WITH POTENTIALS FOR ALL INFOTECH DOMAINS

S12NEW APPLICATIONS SET NEW CHALLENGESLarger Sensor Formats and Speed

Embedding of image Analysis and Vision Tasks at the Sensor

Pipeline for pedestrian detection

Source: SYNOPSIS white paper on embedded vision

Source: AnaFocus Eye-RIS

Range Estimation and Combined 2D/3D

Imaging and Vision

Source: A. Bhandari and R. Raskar

Source: I. Takayanagi and J. Nakamura,

Enlarged Granularity and Responsivity

S13. . . SOME OF THEM RELATED TO LOW-LIGHT VISION

BIOLOGICAL IMAGING

Source: F. Amat, Insight Awards 2013

GLOBAL NUCLEI TRACKING IN THE DROSOPHILA SYNCYTIAL

BLASTODERM

12th and 13th mitotic cycles in the syncytial blastoderm of a Drosophila embryo, recorded with SiMView microscopy

S14

AUTOMOTIVE

Source: BrightEye

. . . SOME OF THEM RELATED TO LOW-LIGHT VISION


NOISE IN IMAGERS




FINAL REMARKS

S16NOISE IN IMAGERS

CONCEPT OF IMAGER NOISE

Whichever perturbation of the absolute or relative pixel values

Deterministic circuit errors: gain error, limited bandwidth,incomplete settling, distortion, . . .

Interferences, external perturbations, crosstalk, . . . Random fluctuations of technological parameters VTO, Cox . . . Microscopic random fluctuations of photons and charges due to

physics and/or defects Data conversion errors Etc.

stdvfpn

=stddsnu

200 400 600 800 1000

200

400

600

800

1000

stdvfpn

=stddsnu

/2

200 400 600 800 1000

200

400

600

800

1000

stdvfpn

=stddsnu

/4

200 400 600 800 1000

200

400

600

800

1000

stdvfpn

=stddsnu

/8

200 400 600 800 1000

200

400

600

800

1000

SPATIAL ARTIFACTS: FPN, PRNU, . . TIME-VARYING ARTIFACTS

S17

Source :J. Nakamura (Ed.), Image Sensors and Signal Processing for Digital Still Cameras, Taylor & Francis 2006

NOISE IN IMAGERS: OVERVIEW OF NOISE TYPES

S18NOISE IN IMAGERS: SPATIAL NOISE

IDEALLY

All pixels identical: same parameter p

All channels identical: same transmittance t

IN PRACTICE

All pixels different

All channels with different transmittance

p11 p12 p13 p1N

p21 p22 p23 p2N

p31 p32 p33 p3N

pM1 pM2 pM3 pMN

t1(.) t2(.) t3 (.) tN (.)

ADDRESSING STRATEGIES

Suitable readout architectures Compensation techniques: CDS,

offset cancellation, . . . Adaptive biasing Optimum component sizing Digitally-assisted analog design Dynamic Element Matching Digital calibration

S19TYPICAL SMART-CIS READOUT ARCHITECTURE

LONIS CIS

S20TEMPORAL NOISE IN THE PHOTON-TO-DN PATH


NOISE IN IMAGERS




FINAL REMARKS

S22TEMPORAL NOISE SOURCES OVERVIEW

e2 e

Shot noise Not relevant for low light conditions

d2 d

Dark charges very small in pinnedphotodiodes (~10e/s)

Negligible for exposures in the rangeof msec

Otherwise, active cooling may be used

Reset Noise (kT/C)

Removed by CDS

Source follower thermalnoise

Source follower low-frequency noises

Noise coming from thetransfer (TX)

S23ADDRESSED NOISE SOURCES

SOURCE FOLLOWER

THERMAL NOISE

White noise.

Sampled every timethe ADC samples thepixel data.

Limited by the LPFtransfer function atpixel output.

SOURCE FOLLOWER

LOW-FREQUENCY

NOISE

Flicker (1/f) noise.

RTS noise.

They change slightlyover the time.

Partially removed byCDS operation.

NOISE COMING FROM

THE TRANSFER (TX)

It is the noise storedin the FD node aftercharge transfer .

Related to theoverlap capacitorbetween photodiodeand transfer gate.

S24TRANSFER NOISE ANALYSIS REDUCTION

Caused by electrons thatremain in the overlap capacitorbetween TX gate and PD

Source : Wegmann 1987

S25TRANSFER NOISE ANALYSIS REDUCTION

Caused by electrons thatremain in the overlap capacitorbetween TX gate and PD

Problem similar to charge feedthrough in SC circuits

Partially handled through control signals: Voltage levels Signal slopes

S26SOURCE FOLLOWER NOISE ANALYSIS

Framework for SF Noise Analysis

White and pink noise contributions

Low-pass filtering of the noise

Additional filtering due toCorrelated Double Sampling

BEAR IN MIND !! CDS may beembedded within the ADC in thecase on ULN readout.

S27

Transfer function with CDS

Output noise power:

By integrating both noise contributions

0.577215

SOURCE FOLLOWER NOISE ANALYSIS

S28SF NOISE CONTROL THROUGH TO

4 2⁄

1

1

1

4 2⁄

► LOW FREQUENCY NOISE IS FILTERED

OUT BY CHANNEL AND CDS

► THE SHORTER TO THE MORE EFFECTIVE

LOW FREQUENCIES FILTERING

To cannot be shortenedarbitrarily due to:

It contains the transfertime (minimum 0.5us)

Enough room for signalsettling must be provided

S29PIXEL NOISE MODEL: DEVIATIONS IN LF BEHAVIOR

LF pixel noise is crucial for low-noise CIS design

Calculations give

Formula not accurate due deviations from the 1/f trend

LF pixel noise depends on several parameters:

CDS time, CMS technique, time inter samples, etc.

Analytical calculations may not be not feasible

For instance, several slopes are obtained for different To values

Empirical noise fitting required for optimized

noise design


NOISE IN IMAGERS




FINAL REMARKS

S31BASIC ADC TYPES

Source: A. Rodríguez-Vázquez @ IMSE CVIS Lab, “CMOS Telecom Data Converters”.Kluwer Academic Publishers, 2003

S32COMPARISON OF ADCS FOR CISS

Source: J.A. Leñero and A. Rodríguez-Vázquez @ IMSE CVIS Lab, “ADCs for ImageSensors: Review and Performance Analysis”. CRC Press, 2016

Cyclic, SAR, andRamp ADCs havelower FoM

Hybrid architecturesprovide large designflexibility

Column-parallel archi-tectures chosen toreview the state-of-the-art

By using the followingFOM

FOM defined in THE

LOWER-THE-BETTER

form

S33LONIS: READOUT CHANNEL ARCHITECTURE

CONVERSION PERFORMED INTO TWO STEPS:

● Shorter conversion time (Tconv)

● Non-significant complexity overhead

● High-accuracy with low hardware overhead

● Second stage errors (noise and mismatch) aredivided by the gain of first stage

● Much better power efficiency, much betterFoM=Power/(Tconvꞏ2ENOB)

● Mismatch among stages must be carefullyaddressed

LONIS CIS READOUT

S34

Measurement according to the EMVA Standard 1288

Temporal Noise (DN14bit) STD total =1.14DN

100 200 300 400 500 600

50

100

150

200

250

300

350

400

450-3

-2

-1

0

1

2

3

r/o-channeltemp. noise of1.14DN14-bit

equivalent to0.9e-rms

LONIS TEMPORAL NOISE MEASUREMENT

S35Lux

Source : [A. Fenigstein et al, IISW 2015]

S36LONIS: OVERALL NOISE DESIGN LEVELS

Readout channel noise < 112μVrms

Strategies for further noise reduction

Semi-empirical modeling of the LF pixelnoise and pixel optimization.

Modification of the ADC architecture toinclude oversampling of the pixel noise

Readout Channel Noise 112uVrms

S37ULN: ADC CONCEPT

2122 DDD N

out

● No Sample-and-Hold; Pixel directly drives the AD,

● Pixel output is oversampled, high-frequency noiseis reduced.

► 1st stage is a SD modulator

► 2d stage is a ramp converter

● Programmable resolution for noise improvement

● CDS realized in 1st stage

S38

Internal CDS: one conversion per row time

Phase exchanged to integrate pixel output inopposite direction for reset and signal, thusperforming CDS operation

At the same time pixel output is oversampled

ULN CIS: ADC FIRST STAGE

S39ULN CIS: ADC SECOND STAGE

Single-slope ramp in second ADC stage

Converts the residue coming from ADC1in internal CDS and external CDS

Digital register

Analogue ramp

Digital ramp (counter)

Output digital

Analog input(Vzero)

en

phi_ro_adc2_sa_d_h

phi_ro_adc2_sa_h

phi_ro_adc2_vcmi_sa_h

SAMPLING IDLE

phi_ro_adc_start

armp_phi_clear

armp_phi_start

scm_sps_adc_last

AD CONVERSION

analog_ramp

Linear ramp

º

digital_ramp

Vzero

Vmax

0

1024

IDLE

phi_ro_adc1_end_d_h

phi_ro_adc2_comp_h

phi_ro_adc2_comp2_h

S40ULN CIS: ADC CALIBRATION

IDEAL SITUATION

● All input-output ranges perfectlymatch

● Conversion error bounded by +/-1LSB

TO-BE-AVOIDED SITUATION

● Due to circuitry errors, rangesdon’t match perfectly

● Large conversion errors show up

● Information is lost due to clipping

● No calibration/correction ispossible

DESIRABLE SITUATION

● Ranges don’t match, but fit in eachother

● Large conversion, but noinformation loss

● Calibration/correction is possible

S41ADC CALIBRATION

S42SELF-ADAPTIVE ERROR CORRECTION

S43

14bits 16 61.44 17.50 19.00 35.24 75.39 0.79 72.32 0.76

15bits 32 42.83 8.75 9.50 17.62 48.08 0.51 48.06 0.51

16bits 64 30.06 4.38 4.75 8.81 31.99 0.34 32.73 0.34

Readout Noise

CG= 95uV/e [e]

Experimental Noise measurements

Quantization

Noise

[uVrms]

Readout Noise

[uVrms]

Readout Noise

CG= 95uV/e [e]

Simulated Noise results

Readout Noise

[uVrms]Readout mode nc

ADC1 Noise

[uVRms]

ADC2 Noise

[uVRms]

Ramp Noise

[uVrms]

2122 DDD N

out

Pixel noise not included in this table

ULN CIS: ADC NOISE PERFORMANCE


NOISE IN IMAGERS


DATA CONVERSION FOR LOW-NOISE CIS


FINAL REMARKS

S45CORRELATED MULTIPLE SAMPLING TECHNIQUE

Accuracy enhanced by averaging M different reset and signal samples

It requires replacing an amplifier by an integrator

Some Observations

Correlated Multiple Sampling is effective for high-frequency noise

Not so much effective for low-frequency noise

By increasing M, the time lag TG + MTo between reset and signal increases as well

Decorrelation of LF noise contributions to reset and signal increases

There is a trade-off affecting M value

S46ILLUSTRATING CMS TRADE-OFF

S47NOISE PERFORMANCE: PIXEL TYPE V0, V1 AND V2

Multi-sampling data assumes 14 bits

ULN ADC Resolution (Nbits)

ULN Noise (uVrms)

Sense ADC Resolution (Nbits)

ULN Noise (e-)

ULN ADC Resolution (Nbits)

Noise in Multi-sampling (e-)

M: Multi-Sampling Factor

Channel readout

14 bits 15 bits 16bits M=1 M=2 M=4 M=8 M=16 M=32

v2 [uVrms] 9.99E‐05 7.58E‐05 6.45E‐05 1.21E‐04 8.99E‐05 6.81E‐05 5.58E‐05 4.86E‐05 4.47E‐05

v2 [e‐] 1.07E+00 8.10E‐01 6.89E‐01 1.30E+00 9.61E‐01 7.28E‐01 5.97E‐01 5.19E‐01 4.78E‐01



v0 [e‐] 1.04E+00 8.57E‐01 7.80E‐01 1.21E+00 9.33E‐01 7.87E‐01 7.06E‐01 6.74E‐01 6.75E‐01



v1[e‐] 1.04E+00 8.52E‐01 7.68E‐01 1.23E+00 9.46E‐01 7.79E‐01 6.93E‐01 6.49E‐01 6.46E‐01

CG v1 [uV/e‐]

108.4E‐6

CG v2 [uV/e‐]

93.6E‐6

CG v0 [uV/e‐]

112.1E‐6

Sense internal CDS Sense Multisampling (Readout Noise included)



3.82E‐09

v2 Nf [V^2/Hz]

1.45E‐09

v0 Nf [V^2/Hz]

4.43E‐09

v1 Nf [V^2/Hz]

v2

v1

v0

S48ILLUSTRATIVE LOW LIGHT CAPTURES

0.396lux

0.00891lux

S490.5eRMS, LARGE FORMAT CIS

S50SUMMARY

Low-noise design at pixel level achieved through:

Pixel noise modeling based on empirical fitting

Optimization of transistor sizes

Proper control of waveform levels and shapes

Two-stage ADC readout channels feature:

Shorter conversion times: 2N2*Tbit vs. 2N*Tbit (Tbit = 2ns in 180nm CMOS)

Second stage noise and errors are attenuated by the Gain of the first stage

Second stage is optimized in power consumption and area, and it remainsin very good FoM:

FoM = Pw/(2^ENOB)*Tconv

FoM = 0.24pJ/LSB per channel in this work ADC FoM =0.6pJ/LSB traditional approach

S51. . . LOOKING BEYOND

BESIDES LOW-NOISE, EXTENSION OF THE TOP BOUNDS OF THE DYNAMIC RANGE IS

NEEDED FOR SOME APPLICATIONS, SUCH AS AUTOMOTIVE

No ghosting artifacts

Source : S. Vargas, G. Liñán, A. Rodríguez-Vázquez@ IMSE CVIS Lab – “A 151dB High Dynamic Range CMOS Image Sensor Chip Architecture with Tone Mapping Compression Embedded in-Pixel”. IEEE Sensor Journal , 2015

S52

VERY LOW ILLUMINATION AND COMBINED 2D/3D IMAGING CAN BE HANDLED BY USING

SPADS

Source: I. Vornicu, R. Carmona, A. Rodríguez-Vázquez@ IMSE CVIS Lab – “Real-Time Inter-Frame Histogram Builder for SPAD Image Sensors”. IEEE Sensors Journal 2018.

. . . LOOKING BEYOND

TIMEFOR

QUESTIONS !!

A. RODRÍGUEZ-VÁZQUEZ

UNIVERSIDAD DE SEVILLA, IMSE/ [email protected]; [email protected]

Research of Angel Rodríguez-Vázquez supported by the SMART CIS3D, Junta de Andalucía P12-TIC-2338 Project

Documents

Large Format, Fast, 0.5erms CIS with Oversampled … · SUB‐ELECTRONLOW‐NOISECMOS IMAGE SENSORS Large Format, Fast, 0.5erms CIS with ... TWO-STAGE ADCFORLOW-NOISECIS