Sparse delay-Doppler image reconstruction under off-grid problem
Author
Teke, Oğuzhan
Gürbüz, A. C.
Arıkan, Orhan
Date
2014-06Source Title
Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, 2014
Publisher
IEEE
Pages
409 - 412
Language
English
Type
Conference PaperItem Usage Stats
127
views
views
136
downloads
downloads
Abstract
Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay-Doppler plane is discretized and FFT techniques are employed to compute matched filter output on this discrete grid. However, for targets whose delay-Doppler values do not coincide with the computation grid, the detection performance degrades considerably. Especially for detecting strong and closely spaced targets this causes miss detections and false alarms. Although compressive sensing based techniques provide sparse and high resolution results at sub-Nyquist sampling rates, straightforward application of these techniques is significantly more sensitive to the off-grid problem. Here a novel and OMP based sparse reconstruction technique with parameter perturbation, named as PPOMP, is proposed for robust delay-Doppler radar processing even under the off-grid case. In the proposed technique, the selected dictionary parameters are perturbed towards directions to decrease the orthogonal residual norm. A new performance metric based on Kull-back-Leibler Divergence (KLD) is proposed to better characterize the error between actual and reconstructed parameter spaces. © 2014 IEEE.
Keywords
Doppler radarFast Fourier transforms
Image reconstruction
Closely-spaced targets
Compressive sensing
Detection performance
Parameter perturbation
Performance metrices
Pulse-Doppler radar
Sparse reconstruction
Sub-Nyquist sampling
Signal processing