Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme

The time of arrival (TOA)-based localization techniques, which need to estimate the delay line-of-sight (LoS) path, have been widely employed in location-aware networks. To achieve a high-accuracy estimation, number multiband-based algorithms proposed recently, exploit channel state information (CSI) measurements over multiple non-contiguous frequency bands. However, best our knowledge, there still lacks an efficient scheme that fully exploits multiband gains when phase distortion factors caused by hardware imperfections are considered, due associated multi-parameter estimation problem contains many local optimums and existing can easily get stuck “bad” optimum. address these issues, we propose novel two-stage global (TSGE) for estimation. In coarse stage, group sparsity structure Turbo Bayesian inference (Turbo-BI) algorithm good initial based on signal model, is transformed from original model absorbing carrier terms. derived fewer thus more stable be achieved than directly using model. Then refined with help results narrow down search range, perform particle swarm optimization-least square (PSO-LS) further improve accuracy. Simulation show TSGE significantly outperforms benchmarks comparative computational complexity.