A Novel Long-time Coherent Integration Method for Highly Maneuverable Target Based on Three-Dimension Parameter Space

Abstract

Radar detection of maneuvering target with complex motions usually results in severe deterioration of performance because of the issues of range migration (RM) and Doppler frequency migration (DFM) within a coherent processing interval. To solve these problems, this paper proposes a novel method without brute-force multi-dimension search procedure. Specifically, the method first develops a parametric minimum entropy optimization model to estimate the fold factor. Then, a bilinear autocorrelation function (BAF) is performed to map the signal to a three-dimension parameter space. Afterwards, scaled Fourier transform (SFT), scaled inverse Fourier transform (SIFT) and Fourier transform (FT) are utilized to complete the signal refocusing. With the estimated parameters, the corresponding phase compensation function can be constructed to eliminate the high-order phase terms and obtain the energy coherent integration. Numerical simulations demonstrate that the proposed method can achieve excellent balance between computational complexity and detection performance.