Radar Error Correction Method Based on Improved Sparrow Search Algorithm

Abstract

Aiming at the problem of the limited application range and low accuracy of existing radar calibration methods, this paper studies the radar calibration method based on cooperative targets, and establishes the integrated radar measurement error model. Then, the improved sparrow search algorithm (ISSA) is used to estimate the systematic error, so as to avoid the loss of partial accuracy caused by the process of approximating the nonlinear equation to the linear equation, thus improving the radar calibration effect. The sparrow search algorithm (SSA) is improved through integrating various strategies, and the convergence speed and stability of the algorithm are also improved. The simulation results show that the ISSA can solve radar systematic errors more accurately than the generalized least square method, Kalman filter, and SSA. It takes less time the than SSA and has a certain stability and real-time performance. The radar measurement error after correction is obviously smaller than that before correction, indicating that the proposed method is feasible and effective.