Radar detection and fast motion parameter estimation for complex manoeuvering targets at high speed and acceleration

Abstract

Abstract Coherent integration of complex manoeuvering targets at high speed and acceleration causes range and Doppler frequency migration and lead to large computational burdens and parameter estimation error. To solve this, the geometric‐auxiliary location rotation transform (GLRT), fast parameter estimation method, and periodic, scaled generalised, high‐order ambiguity function (PSGHAF) were proposed for this study. The quadratic range migration was corrected using the second‐order keystone transform. The GLRT uses the geometrical relationship between the rotation angle and trajectory projection to estimate the velocity and initial range in different noise environments without searching for multidimensional parameters. Thereafter, the high‐acceleration and jerk estimations of the target signal are obtained using PSGHAF, which uses the periodicity of discrete Fourier transformation (DFT) to extend the estimation scope of acceleration. This avoids estimation errors without changing the radar system parameters. Compared with others, the proposed algorithm has a lower computational complexity and improved detection performance. Numerical simulations and real data from unmanned aerial vehicles demonstrate the efficacy of the proposed solution.

Keywords

• geometric‐auxiliary location rotation transform
• long‐time coherent integration
• periodic scaled generalised high‐order ambiguity function
• range migration