Joint Association and Registration in a Multiradar System for Migratory Insect Track Observation

Abstract

The migration of insects is an important way of material and energy transfer in nature. The accurate multitargets’ tracks are beneficial for studying insect flight mechanisms. Radar has been widely used in insect observation. Compared with a single radar system, a multiradar system can provide measurements from more dimensions and produce more accurate flight tracks. However, for insect observation, there are lots of targets and outliers in the measurement sets, which may challenge the measurement-to-measurement association between different radars. In addition, sensor bias estimation is needed to achieve good association and fusion results. We propose a joint association and registration method to simultaneously acquire bias estimates and association results for insect observation. The Gaussian-Seidel method is applied to solve the nonlinear least square bias estimate problem without any approximation. The Cramér-Rao bound is derived in the article. The simulation results show that our method can achieve the best association performance for different scenarios among the competing approaches, and bias estimation results are insensitive to the bias values, that can improve the accuracy of the fusion tracks.