Sensor management for multi-target tracking via multi-Bernoulli filtering

Sensor management for multi-target tracking via Multi-Bernoulli filtering

In multi-object stochastic systems, the issue of sensor management is a theoretically and computationally challenging problem. In this paper, we present a novel random finite set (RFS) approach to the multi-target sensor management problem within the partially observed Markov decision process (POMDP) framework. The multi-target state is modelled as a multi-Bernoulli RFS, and the multi-Bernoulli...

Particle Filtering for Multi-target Tracking and Sensor Management

Decentralized and Cooperative Multi-Sensor Multi-Target Tracking With Asynchronous Bearing Measurements

Bearings only tracking is a challenging issue with many applications in military and commercial areas. In distributed multi-sensor multi-target bearings only tracking, sensors are far from each other, but are exchanging data using telecommunication equipment. In addition to the general benefits of distributed systems, this tracking system has another important advantage: if the sensors are suff...

Multi-Bernoulli sensor-selection for multi-target tracking with unknown clutter and detection profiles

A new sensor-selection solution within a Multi-Bernoulli-based multi-target tracking framework is presented. The proposed method is especially designed for the general multi-target tracking case with no prior knowledge of the clutter distribution or the probability of detection, and uses a new task-driven objective function for this purpose. Step-by-step sequential Monte Carlo implementation of...

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the pe...