Multisource Spatiotemporal Tracking Using Sparse Large Aperture Arrays

In this paper, a multisource tracking technique is proposed using a sparse large aperture array of passive sensors of known geometry. First, a novel spherical-spatiotemporal-state-space model is introduced incorporating target ranges, directions, and Doppler effects in conjunction with the array geometry. Subsequently, this array of sensors is integrated with an extended Kalman filter (EKF), defined as the arrayed EKF, to track the trajectory of multiple mobile sources. In addition, a recursive lower bound on the performance of the proposed tracking method is obtained based on the posterior Cramer–Rao bound. Computer simulation studies show that the proposed approach can track the locations of sources, as these move in space, with a very high accuracy.