Through-the-wall radar imaging algorithm for moving target under wall parameter uncertainties

In order to solve the problems of slow imaging speed and poor reconstruction accuracy of wall parameters under the condition of wall parameter fuzziness, an improved limited Broyden–Fletcher–Goldfarb–Shanno-particle swarm optimisation (LBFGS-PSO) algorithm was proposed. The LBFGS-PSO algorithm model solves the problems of slow calculation speed and large errors of the traditional quasi-Newton algorithm and particle swarm algorithm. The algorithm combined with block orthogonal matching pursuit algorithm can not only accurately reconstruct the position of the sidewall, but also can use the multi-path information to accurately reconstruct the moving target and the stationary target. Compared with the traditional BFGS algorithm and PSO algorithm, the proposed algorithm can reduce the calculation time and provide more accurate estimation results. Simulation results and data analysis verify the performance of the proposed algorithm.