A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors

Abstract

A robust transmit-receive angle imaging method for bistatic MIMO radar based on compressed sensing is proposed. A new imaging model with array gain and phase error is established. The array gain error and phase error were modeled as a random interference for observation matrix by mathematical derivation. A constraint of observation matrix error is constructed in optimization problem of sparse recovery to reduce the effect of the interference of observation matrix. Then, the iterative algorithm of the optimization problems is derived. The proposed recovery method is more robust than the existed method in small samples, especially in the case of one snapshot. It is applicable in the case of relatively small array gain and phase errors. Simulation results confirm the effectiveness of the proposed method.

Sparsity-Based Robust Bistatic MIMO Radar Imaging in the Presence of Array Errors

“…It can be seen in Figure 4 that the iterative method [15] and Lasso method work slightly better than the constrained optimization method [14] and the proposed method achieves much better performance than the iterative method [15] and Lasso method. Simulations show that the MSEs of the constrained optimization method [14], the iterative method [15], the Lasso method, and the proposed method are 14.93, 11.07, 12.40, and 4.78, respectively. Figure 5 shows the MSE and PRC of the four methods, where the error parameter ε changes from 0.2 to 0.8 with the interval 0.02.…”

“…In this section, we examine the performance of the proposed method in comparison with that of the Lasso method and the methods proposed in [14] and [15]. We use the mean square error (MSE) and performance recovery coefficient (PRC) with the following definitions to evaluate the reconstruction quality:…”

“…Figure 3 shows the computation time of each algorithm with different numbers of antennas. It can be seen that the proposed method takes less time than the iterative method in [15] but takes longer time than the constrained optimization method [14] and Lasso method. Figure 4 shows the results of the image recovery by using different methods.…”

“…In the bistatic MIMO radar, the direction of arrival (DOA) and the direction of departure (DOD) of targets can be obtained at the same time by processing the received signals, and it has been employed to identify and locate multiple targets [9,10], clutter cancellation [11,12], and imaging [13][14][15]. Nevertheless, due to the presence of the gain and phase errors of the transmitting array and receiving array, the imaging quality and detection accuracy of these techniques can deteriorate seriously.…”

“…However, the method does not consider the array phase errors and does not work well with a single snapshot. In [15], a transmit-receive angle imaging method is proposed, but its complexity is high and its performance degrades severely when the gain-phase errors are relatively large. In this work, we propose a robust sparse recovery method for transmit-receive angle imaging in the bistatic MIMO radar.…”