Abstract
Polarization-sensitive array (PSA) processing works well in navigation system applications for interference mitigation. However, the fixed configuration of conventional PSA increases the computational burden of subsequent adaptive array processing and can even be inefficient and redundant in some cases. Furthermore, since the radio frequency (RF) front end is more costly than the antenna, it is urgent to exploit a PSA reconfiguration method that can lower the cost of array design and achieve sufficiently good anti-interference performance when employing fewer RF front ends and antennas. In this paper, a PSA reconfiguration technique maximizing the signal to interference plus noise ratio (SINR) is presented to solve the problem. Combining with adaptive processing, we derive the formula between the SINR and the polarization-spatial correlation coefficient (PSCC), thereby building the mathematical model with minimizing PSCC as the objective function. Then, the lower bound of the optimal PSCC, gained by the Lagrange Dual Relaxation method, is utilized to guide the selection of the antenna number. Finally, we adopt an iterative correlation measurement (ICM) approach to confirm the antenna element position of the optimal subarray with the minimum PSCC. Numerical simulations illustrate the effectiveness and correctness of the proposed technique and derived theoretical results.
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