Abstract
In this paper we present a new approach to Received-Signal-Strength-Indicator (RSSI)-based multi-target tracking. In order to effectively deal with this inherently high-dimensional problem, the approach leverages space decomposition through cooperative distributed processing. The core system is composed of multiple agents where each agent is assigned to track a particular target. The agents exchange information, and based on it they treat the RSSI from the targets they do not track as measurement interference. We present computer simulations that compare the new method with conventional approaches in settings with two and 20 targets, respectively. They demonstrate the improvements of the proposed method in tracking a relatively large number of targets.
| Original language | English |
|---|---|
| Article number | 7130678 |
| Pages (from-to) | 5033-5044 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Signal Processing |
| Volume | 63 |
| Issue number | 19 |
| DOIs | |
| State | Published - Oct 1 2015 |
Keywords
- Bayesian estimation
- mobile sensor networks
- multi-agent systems
- multiple-target tracking
- particle filtering
- unscented Kalman filtering
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