Multi-Bernoulli Sensor-Control via Minimization of Expected Estimation Errors

TL;DR

This paper introduces a sensor-control approach for multi-target tracking that minimizes a new estimation error-based cost function, improving robustness and computation time over existing methods.

Contribution

It proposes a novel sensor-control method based on a multi-Bernoulli filter that optimizes sensor placement by minimizing an estimation error cost function.

Findings

Outperforms state-of-the-art methods in computation time

Demonstrates robustness to clutter

Maintains similar accuracy levels

Abstract

This paper presents a sensor-control method for choosing the best next state of the sensor(s), that provide(s) accurate estimation results in a multi-target tracking application. The proposed solution is formulated for a multi-Bernoulli filter and works via minimization of a new estimation error-based cost function. Simulation results demonstrate that the proposed method can outperform the state-of-the-art methods in terms of computation time and robustness to clutter while delivering similar accuracy.