SOURCEFORGE » RALF

h1. Examples (radar)

Hereafter you will find :
* experimental data set that were obtained with SDR-radar systems;
* processing output examples.

h2. Experimental radar data set from SDR-KIT 2400AD2 Ancortek

Useful information about the SDR-KIT 2400AD2 Ancortek can be found at http://ancortek.com/
!{width:150px}resized-im2-radar.jpg! !{width:150px}resized-im1-radar-screen.jpg!
IQ data are recorded in MAT-file and can be read with the Matlab code attachment:"readdata_radar2400AD2.m"
IQ imbalance processing is likely to be needed.

table(centered).
|=. Data file |=. Waveform|=. Carrier frequency (GHz)|=. Bandwidth (GHz)|=. PRF (ms)|=. Samples per sweep (-)|=.Scenario description|
| attachment:"2017-02-09-10-34-32.mat"| LFMCW| 25| 2|1 | 128| RC car receding in corridor (non moving environment)|
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| attachment:"2017-07-27-16-57-05.mat"| LFMCW| 24.75| 1.5|4 | 128| No target, corridor with plants on ground in range-gate ca. 20-30 with hidden fan creating a windy environment|
| attachment:"2017-07-27-17-01-31.mat"| LFMCW| 24.75| 1.5|4 | 128| No target, corridor with plants on ground in range-gate ca. 20-30 with hidden fan off|
| attachment:"2017-07-27-17-07-46.mat"| LFMCW| 24.75| 1.5|4 | 128| RC car receding-closing in corridor with plants on ground in range-gate ca. 20-30 with hidden fan creating a windy environment
attachment:"VID_20170727_170631_forge.mp4"|
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| attachment:"2017-07-27-13-57-54.mat"| LFMCW| 25|2|4|256| No target, corridor with plants on ground in range-gate ca. 54-82 with hidden fan creating a windy environment|
| attachment:"2017-07-27-14-05-00.mat"| LFMCW| 25|2|4|256| No target, corridor with plants on ground in range-gate ca. 54-82 with hidden fan off|
| attachment:"2017-07-27-13-42-41.mat"| LFMCW| 24.75| 1.5|4 | 128| RC car receding-closing in corridor with plants on ground in range-gate ca. 54-82 with hidden fan creating a windy environment
attachment:"VID_20170727_134114_forge.mp4"|

h2. Examples of processing outputs output

h3. Deramping processing

(section in construction)

h3. Doppler processing

(section in construction)

h3. Widedand processing

* Processing outputs of Bayesian sparse representation techniques [BidTAES2019]. [1]
In these figures, diffuse clutter is present at the selected range gates. The RC car is receding with a velocity approximately equal to $-v_a$.
The target is well estimated in the blind velocity with the sparse technique AROFF that jointly estimate the diffuse clutter and the target with its off-grid.

|=. Outputs| Scenario|
|!{width:700px}movie-ssr-20170727134241.gif!|
** dataset: 2017-07-27-13-42-41.mat
** transparent background: coherent summation for wideband radar
** diamond: output of sparse representation
* WON sparse technique assumes white noise and on-grid targets.
* WOFF sparse technique assumes white noise and off-grid targets.
* ARON sparse technique assumes autoregressive-colored noise and on-grid targets.
* AROFF sparse technique assumes autoregressive-colored noise and off-grid targets.
* The MMSE (Minimum Mean Square Error) estimator of target scene ** va is depicted.
$v_a$ is the ambiguous velocity|

h2. References

* [BidTAES2019] Stéphanie Bidon, Marie Lasserre, and François Le Chevalier. Unambiguous sparse recovery of migrating targets with a robustified Bayesian model. IEEE Transactions on Aerospace and Electronic Systems, 55(1) :108–123, Feb 2019. http://oatao.univ-toulouse.fr/22968/ velocity
!{width:700px}movie-ssr-20170727134241.gif!