JOURNAL ARTICLE

A smoothing rao-blackwellized particle filter for tracking a highly-maneuverable target

Abstract

In this paper we apply a new smoothing Rao-Blackwellized particle filter to track a highly maneuverable target in a multiple-sensors network. The scenario of a highly-maneuverable target moving through a field of multiple sensors is addressed. The target is tracked through the sensors filed using both Rao-Blackwellized particle filter and the proposed smoothing filter. In a simulation comparison, the smoothing Rao-Blackwellized particle filter yields performance improvements when tracking a highly-maneuverable target.

Keywords:
Smoothing Particle filter Tracking (education) Filter (signal processing) Computer science Particle (ecology) Control theory (sociology) Artificial intelligence Computer vision Psychology Geology

Metrics

3
Cited By
0.38
FWCI (Field Weighted Citation Impact)
11
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Underwater Acoustics Research
Physical Sciences →  Earth and Planetary Sciences →  Oceanography
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
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