Next Article in Journal
The Study of Cross-layer Optimization for Wireless Rechargeable Sensor Networks Implemented in Coal Mines
Previous Article in Journal
A Novel RFID-Based Sensing Method for Low-Cost Bolt Loosening Monitoring
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(2), 169; doi:10.3390/s16020169

Multi-Target Joint Detection and Estimation Error Bound for the Sensor with Clutter and Missed Detection

Ministry of Education Key Laboratory for Intelligent Networks and Network Security (MOE KLINNS), College of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Academic Editor: Fabrizio Lamberti
Received: 18 November 2015 / Revised: 8 January 2016 / Accepted: 21 January 2016 / Published: 28 January 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [324 KB, uploaded 28 January 2016]   |  

Abstract

The error bound is a typical measure of the limiting performance of all filters for the given sensor measurement setting. This is of practical importance in guiding the design and management of sensors to improve target tracking performance. Within the random finite set (RFS) framework, an error bound for joint detection and estimation (JDE) of multiple targets using a single sensor with clutter and missed detection is developed by using multi-Bernoulli or Poisson approximation to multi-target Bayes recursion. Here, JDE refers to jointly estimating the number and states of targets from a sequence of sensor measurements. In order to obtain the results of this paper, all detectors and estimators are restricted to maximum a posteriori (MAP) detectors and unbiased estimators, and the second-order optimal sub-pattern assignment (OSPA) distance is used to measure the error metric between the true and estimated state sets. The simulation results show that clutter density and detection probability have significant impact on the error bound, and the effectiveness of the proposed bound is verified by indicating the performance limitations of the single-sensor probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters for various clutter densities and detection probabilities. View Full-Text
Keywords: performance evaluation; error bound; multi-target tracking; joint detection and estimation; random finite set performance evaluation; error bound; multi-target tracking; joint detection and estimation; random finite set
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Lian, F.; Zhang, G.-H.; Duan, Z.-S.; Han, C.-Z. Multi-Target Joint Detection and Estimation Error Bound for the Sensor with Clutter and Missed Detection. Sensors 2016, 16, 169.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top