Abstract
Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed received signals and then we propose a new measurement matrix design for our 2D compressive sensing model that is based on minimizing the coherence of sensing matrix using gradient descent algorithm. The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.
Highlights
Compressive sensing (CS) is a signal processing method for reconstructing a signal that is sparse in a specific domain [1, 2]
We introduce a 2D signal model in CS for a collocated Multiple-input multiple-output (MIMO) radar with point targets, and we improve the efficiency of this 2D MIMO radar model by proposing a measurement matrix design using gradient decent algorithm (MMDGD) in which the mutual coherence (MC) of sensing matrix is minimized
Our proposed 2D-MMDGD method leads to a nonlinear problem and there is no guarantee that we find its global minimum, its performance is always better than Gaussian random measurement matrix (GRMM)
Summary
Compressive sensing (CS) is a signal processing method for reconstructing a signal that is sparse in a specific domain [1, 2]. In [32], a method for optimizing the measurement matrix of MIMO radar systems is proposed based on two different criterions; first one is to minimize the summation of coherence of cross columns in the sensing matrix plus maximize the signal-to-interference ratio (SCSM + SIR), and the second criterion is to maximize SIR by imposing a special structure on the measurement matrix. We introduce a 2D signal model in CS for a collocated MIMO radar with point targets, and we improve the efficiency of this 2D MIMO radar model by proposing a measurement matrix design using gradient decent algorithm (MMDGD) in which the MC of sensing matrix is minimized. The compressed received signal in the mth antenna returned from the pth transmitted pulse can be arranged in an observation vector, ypm ∈ CM × 1 as follows: ypm φpm
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