Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar

Costanzo, Sandra

doi:10.1155/2016/3137146

Cited by 2 publications

(2 citation statements)

References 15 publications

(27 reference statements)

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“…Moreover, wideband waveforms may bring difficulties on target detection due to the energy being distributed along different range cells and the unknown range migration among different high range resolution profiles (HRRPs) [1]. Therefore, narrowband radar systems are still widely used in air search radars [1,11,12]. Though different aircraft in MAF may not be separated along the low range resolution profiles, different Doppler parameters, which are caused by different positions and motions of targets during a long time on target (TOT), provide a new approach for MAF identification [1,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…Fortunately, as the number of aircraft is limited, the MCS can be regarded as sparse in the whole parametric space. Therefore, in this paper the MAF identification is investigated by introducing sparse recovery (SR), which is recently discussed in radar area, especially for synthetic aperture radar (SAR) imaging [11,12,15,16,17,18,19,20]. The SR theory indicates that if a signal is sparse on some basis, it can be exactly reconstructed from limited samples with high probability.…”

Section: Introductionmentioning

confidence: 99%

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Identification-While-Scanning of a Multi-Aircraft Formation Based on Sparse Recovery for Narrowband Radar

Jiang

Peng

et al. 2016

Sensors

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It is known that the identification performance of a multi-aircraft formation (MAF) of narrowband radar mainly depends on the time on target (TOT). To realize the identification task in one rotated scan with limited TOT, the paper proposes a novel identification-while-scanning (IWS) method based on sparse recovery to maintain high rotating speed and super-resolution for MAF identification, simultaneously. First, a multiple chirp signal model is established for MAF in a single scan, where different aircraft may have different Doppler centers and Doppler rates. Second, based on the sparsity of MAF in the Doppler parameter space, a novel hierarchical basis pursuit (HBP) method is proposed to obtain satisfactory sparse recovery performance as well as high computational efficiency. Furthermore, the parameter estimation performance of the proposed IWS identification method is analyzed with respect to recovery condition, signal-to-noise ratio and TOT. It is shown that an MAF can be effectively identified via HBP with a TOT of only about one hundred microseconds for IWS applications. Finally, some numerical experiment results are provided to demonstrate the effectiveness of the proposed method based on both simulated and real measured data.

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