Track - Before- Detect Labeled Multi - Bernoulli Filter for Multi- Target Bearing-Only Tracking using an Autonomous Underwater Vehicle

This paper considers an autonomous underwater vehicle (AUV) mounted with an array of sensors to detect the presence of multiple targets and estimate their relative locations. We propose a track-before-detect labeled multi-Bernoulli filter, which directly utilizes the signals received from the sensor array as the measurement in the form of a sample-covariance matrix (SCM). Tractable filtering equations are derived by using a change of variable and complex inverse-Wishart approximation. Simulation results demonstrate the improved performance of the proposed filter in challenge scenarios of low signal-to-noise ratio and multiple target crossing.