Sparse delay-Doppler image reconstruction under off-grid problem

Abstract

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 subNyquist 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 KullbackLeibler Divergence (KLD) is proposed to better characterize the error between actual and reconstructed parameter spaces.

Off-grid sparse FD-MIMO image reconstruction by using improved FOCUSS technique

“…Assuming that the bandwidth of the transmitted signal (4) where m dt and n dr represent the spacing between the th m and first transmitter, the th n and first receiver.…”

“…The focus of CS is solving the underdetermined case where the number of measurements is less than the number of unknowns which is very important in decreasing the required amount of data to tolerable levels in radar applications [4]. Based on CS theory, we can achieve higher-resolution imaging result by using prior information on the sparsity of the target.…”

Atomic Norm-Based DOA Estimation with Dual-Polarized Radar

“…In [29], a new parameter-refined orthogonal matching pursuit (OMP) method was proposed to jointly estimate the off-grid positions and reflectivities of true scatterers. A new OMP-based sparse reconstruction method with parameter perturbation, named as PPOMP, was proposed in [30], in the delay-Doppler radar with the off-grid error. Additionally, in [31], a new image-focusing algorithm was given for sparsity-driven radar to image the rotating targets, and also to consider the off-grid scatterers.…”