Return
Low-complexity multi-target localization via multi-BS sensing
DOI:10.1016/j.dcan.2024.11.002.png)
Abstract
En 中文
Integrated Sensing and Communication (ISAC) is envisioned as a promising technology for Sixth-Generation (6G) wireless communications, which enables simultaneous high-rate communication and high-precision target localization. Compared to independent sensing and communication modules, dual-function ISAC could leverage the strengths of both communication and sensing in order to achieve cooperative gains. When considering the communication core network, ISAC system facilitates multiple communication devices to collaborate for networked sensing. This paper investigates such kind of cooperative ISAC systems with distributed transmitters and receivers to support non-connected and multi-target localization. Specifically, we introduce a Time of Arrival (TOA) based multi-target localization scheme, which leverages the bi-static range measurements between the transmitter, target, and receiver channels in order to achieve elliptical localization. To obtain the low-complexity localization, a two-stage search-refine localization methodology is proposed. In the first stage, we propose a Successive Greedy Grid-Search (SGGS) algorithm and a Successive-Cancellation-List Grid-Search (SCLGS) algorithm to address the Measurement-to-Target Association (MTA) problem with relatively low computational complexity. In the second stage, a linear approximation refinement algorithm is derived to facilitate high-precision localization. Simulation results are presented to validate the effectiveness and superiority of our proposed multi-target localization method.
Keywords:
Integrated sensing and communication
Multi-target localization
Measurement-to-target association problem
Bi-static range measurement
Low complexity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.5
Papers:
406
Citations:
3.5K

