Simultaneous tracking and long time integration for detection in collaborative array radars

In this work, we focus on the detection of manoeuvring low signal to noise ratio (SNR) objects in multiple collaborating radars. Collaboration involves having the knowledge of the locations of the transmitters and their transmission characteristics up to a synchronisation term which has to be estimated during the operation. We propose a local processing algorithm, which performs simultaneous trajectory estimation and long time integration of pulse returns in both the local channel and the remote channels. The synchronisation of the remote channels is achieved by simultaneously diverting beams towards both the tested point of detection and the transmitters. Detection is made by using a Neyman-Pearson test. Overall, this scheme enables us to exploit a statistical MIMO effect for the objects in the field of view and integrate multiple pulse returns while taking into account the object trajectory leading to the capability of detecting low SNR and manoeuvring objects. We demonstrate the efficacy of our approach through simulations.