Abstract
In this article, we address the problem of distributed detection of a noncooperative (unknown emitted signal) target with a wireless sensor network. When the target is present, sensors observe a (unknown) deterministic signal with attenuation depending on the unknown distance between the sensor and the target, multiplicative fading, and additive Gaussian noise. To model energy-constrained operations within Internet of Things, one-bit sensor measurement quantization is employed and two strategies for quantization are investigated. The fusion center receives sensor bits via noisy binary symmetric channels and provides a more accurate global inference. Such a model leads to a test with nuisances (i.e., the target position $\boldsymbol {x}_{T}$ ) observable only under $\mathcal {H}_{1}$ hypothesis. Davies' framework is exploited herein to design the generalized forms of Rao and locally optimum detection (LOD) tests. For our generalized Rao and LOD approaches, a heuristic approach for threshold optimization is also proposed. The simulation results confirm the promising performance of our proposed approaches.
Original language | English (US) |
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Article number | 9344705 |
Pages (from-to) | 9059-9071 |
Number of pages | 13 |
Journal | IEEE Internet of Things Journal |
Volume | 8 |
Issue number | 11 |
DOIs | |
State | Published - Jun 1 2021 |
Keywords
- Distributed detection (DD)
- Internet of Things (IoT)
- Rao test
- generalized-likelihood ratio test
- locally optimum detection (LOD)
- wireless sensor networks (WSNs)
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications