Abstract

In this paper we will consider several algorithms for tracking closely spaced objects. In particular we will concentrate on various particle filter implementations. One particular problem when using a joint multi target particle filter is the so-called mixed labelling problem. This problem amounts to the fact that different particles will have a different labelling w.r.t. target identity. The combination of the mixed labelling problem and naïve or straightforward track extraction leads to performance degradation. This will be illustrated and alternative methods to alleviate this effect will be presented.

Keywords:
Particle filter Tracking (education) Computer science Particle (ecology) Artificial intelligence Kalman filter Geology

Metrics

13
Cited By
1.55
FWCI (Field Weighted Citation Impact)
12
Refs
0.86
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
Infrared Target Detection Methodologies
Physical Sciences →  Engineering →  Aerospace Engineering
Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering

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