Modified maximum likelihood space registration method for shipborne multi-radar signal processing

Abstract

Aiming at the spatial registration problem for networking of multi-platform shipborne radars, a modified maximum likelihood (MML) absolute registration algorithm based on singular value decomposition (SVD) is proposed. Firstly, the four major biases (radar detection biases, platform positioning biases, attitude biases, and baseline conversion biases) which affect shipborne radar detection are analyzed, and an equivalent model of shipborne radar detection biases is established to make the bias parameters more efficiently. Secondly, the maximum likelihood registration method is improved. According to the singular value decomposition, the conditional index is used to evaluate the observability in the maximum likelihood registration method in realtime, and the abnormal conditional index is corrected to effectively reduce the fluctuation of the bias estimation. Finally, the simulation results of two different scenarios are conducted, and the results show that the new method has significant improvements in estimation accuracy and algorithm stability compared with the existing algorithms.