Multi-target tracking using multi-modal sensing withwaveform configuration

We investigated the joint multi-modal operation of the asymmetric character of the fields of view of radar and electro optical (EO) sensors for multi-target tracking applications. We proposed a joint multi-modal sensing mode based on using dynamic agility selection to optimize the tracking performance of multiple maneuvering targets. The proposed method jointly designs waveforms for radar sensing and resolution switching modes for EO sensing, when both sensor measurements experience high false alarm rates. Rao-Blackwellized particle filtering is used to track an unknown number of targets within an adaptive framework that yields the optimized joint sensor configuration. We demonstrated the performance of the proposed adaptive tracking system using numerical simulations.

1. INTRODUCTION

When complementary information from different types of sensors is appropriately combined, the application-specific performance is expected to increase when compared to each sensor's performance separately. For joint dynamic target tracking (using active radio frequency (RF) radar sensors) and target identification (using passive EO sensors), the combined sensor capabilities have the potential of improving the performance over either sensor capability. For example, the kinematic features for target tracking from the RF sensor and the physical features for target identification from the EO sensor can be combined to increase the joint target tracking performance.