We consider decentralized detection (DD) of an uncooperative moving target via wireless sensor networks (WSNs), measured in zero-mean unimodal noise. To address energy and bandwidth limitations, the sensors use multi-level quantizers. The encoded bits are then reported to a fusion center (FC) via binary symmetric channels. Herein, we propose a generalized Rao (G-Rao) test as a simpler alternative to the generalized likelihood ratio test (GLRT). Then, at the FC, a truncated one-sided sequential (TOS) test rule is considered in addition to the fixed-sample-size (FSS) manner. Further, the asymptotic performance of a trajectory-clairvoyant (multi-bit) Rao test is leveraged to develop an offline and per-sensor quantizer design. Detection gain measures are also introduced to assess resolution improvements. Simulations show the appeal of G-Rao test with respect to the GLRT, and the gain in detection by using multiple bits for quantization, as well as the advantage of the sequential detection approach.
Multi-Bit & Sequential Decentralized Detection of a Noncooperative Moving Target through a Generalized Rao Test / Cheng, X.; Ciuonzo, D.; Rossi, P. S.; Wang, X.; Wang, W.. - In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS. - ISSN 2373-776X. - 7:(2021), pp. 740-753. [10.1109/TSIPN.2021.3126930]
Multi-Bit & Sequential Decentralized Detection of a Noncooperative Moving Target through a Generalized Rao Test
Ciuonzo D.;
2021
Abstract
We consider decentralized detection (DD) of an uncooperative moving target via wireless sensor networks (WSNs), measured in zero-mean unimodal noise. To address energy and bandwidth limitations, the sensors use multi-level quantizers. The encoded bits are then reported to a fusion center (FC) via binary symmetric channels. Herein, we propose a generalized Rao (G-Rao) test as a simpler alternative to the generalized likelihood ratio test (GLRT). Then, at the FC, a truncated one-sided sequential (TOS) test rule is considered in addition to the fixed-sample-size (FSS) manner. Further, the asymptotic performance of a trajectory-clairvoyant (multi-bit) Rao test is leveraged to develop an offline and per-sensor quantizer design. Detection gain measures are also introduced to assess resolution improvements. Simulations show the appeal of G-Rao test with respect to the GLRT, and the gain in detection by using multiple bits for quantization, as well as the advantage of the sequential detection approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.