The development of high-tech, dim, small targets, such as drones and cruise missiles, brings great challenges to radar multi-target tracking (MTT), making it necessary extend the beam dwell time obtain a high signal-to-noise ratio (SNR). In order solve problem sampling variation exacerbated by extending when detecting weak sector-matching (SM) PHD filter is proposed, which combines actual syste...

Stochastic geometry is an established branch of mathematics that studies uncertainty in geometric structures [1], [2] and is, thus, a befitting framework for autonomous robotic mapping and the well known Simultaneous Localization and Mapping (SLAM) problem, where the fundamental concern is succinctly captured in the title of the 1988 seminal paper by Durrant-Whyte, ”Uncertain geometry in roboti...

Tracking multiple objects is a challenging problem for an automated system, with applications in many domains. Typically the system must be able to represent the posterior distribution of the state of the targets, using a recursive algorithm that takes information from noisy measurements. However, in many important cases the number of targets is also unknown, and has also to be estimated from d...

In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density ...

The random-set framework for multiple target tracking offers a distinct alternative to the traditional approach to multiple target tracking by treating the collections of individual targets and observations as finite-sets. The multi-target state is predicted and updated recursively based on the set-valued observation. The complexity of computing the multi-target recursion grows exponentially wi...

In radar systems, tracking targets in low signal-to-noise ratio (SNR) environments is a very important task. There are some algorithms designed for multitarget tracking. Their performances, however, are not satisfactory in low SNR environments. Track-before-detect (TBD) algorithms have been developed as a class of improved methods for tracking in low SNR environments. However, multitarget TBD i...