Compressed sensing digital receiver and orthogonal reconstructing algorithm for wideband ISAR radar

Abstract

This paper proposes a novel design of intermediate frequency (IF) digital receiver for wideband inverse synthetic aperture radar (ISAR) based on compressed sensing (CS). For the convenience in engineering application, we use random sampling in the digital receiver and make it possible to digitize the wideband IF signal using a commercial off-the-shelf analog-to-digital converter with sub-Nyquist sample rate. Besides, a novel basis for the sparse representation of real-valued ISAR radar echoes is built in this paper, and an orthogonal CS reconstructing algorithm is proposed based on this. Using our proposed method, the complex-valued range profile of target can be directly reconstructed from the subsampled real raw echo. The phase information of target range profile, which is very important for the coherent processing in ISAR imaging, is well reserved during the reconstruction. As a result, the down converter and matched filter, which are essential in conventional radar receiver, can be eliminated in our CS digital receiver. A series of simulation validates our design and demonstrates the feasibility of the sub-Nyquist sampling. The simulation results of ISAR imaging verify the validity and superiority of the proposed orthogonal reconstructing method.

Image registration for InISAR based on joint translational motion compensation

“…Herein, we can conclude that both new registration method and registration method based on correlation coefficient are effective in simulation, while the new method is more precise and significantly more efficient. ISAR image registration and InISAR imaging under more complicated conditions such as compressed sensing [17] are our following work.…”

An Adaptive Dwell Scheduling Algorithm for Digital Array Radar Based on Pulse Interleaving

“…The total simulation time is 6s, the scheduling interval length is 50ms, and the radar can provide an average power of 400W. Traditional phased array radar algorithm (traditional algorithm) [8], the pulse interleaving scheduling algorithm(simple task algorithm) which does not consider the imaging tasks [9] and the adaptive dwell scheduling algorithm proposed in this paper (proposed algorithm) are compared in the simulation. Comparison curves of three different algorithms are shown in Fig.…”

Improved RIP-based performance guarantees for multipath matching pursuit

“…Compressed sensing (CS) is a novel sampling paradigm in signal processing that guarantees the reconstruction of a sparse or compressible signal with a lower sampling rate than the Nyquist rate [1]. It can significantly reduce the amount of data that must be stored and transmitted, and has been successfully applied to radar, communications, and other fields [2][3][4][5].…”