ISAR Speed Compensation Algorithm for High-speed Moving Target Based on Simulate Anneal

When the high-speed moving target is imaging in inverse synthetic aperture radar (ISAR), the echoes are subject to inner-pulse Doppler modulation, resulting in a one-dimensional range profile broadening of the main lobe, which will affect subsequent target imaging and recognition. Aiming at the ISAR imaging of high-speed moving target, this paper proposed an inner-pulse speed compensation algorithm. Firstly, the high-speed moving target echo model is built, and the influence of high-speed motion on the chirp rate of the echo is analyzed. Secondly, the inner-pulse speed compensation of the echo is completed based on the phase compensation method, so that the echo signal satisfies the “stop-go" model requirement. Then, let the minimum entropy of the waveform as the objective function, a target speed estimation algorithm based on simulate anneal (SA) is proposed. Finally, the simulation experiment is carried out to verify the effectiveness of the proposed algorithm. The SA algorithm used to estimate the target speed in this paper is a global optimization algorithm. It is not necessary to set the speed search range, and the algorithm has no requirement for speed prediction. Moreover, the waveform entropy is used as the objective function for optimization, and the useful information of the echo is fully utilized, which makes the algorithm has the advantages of high precision.