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Adaptive Range-Based Target Localization Using Diffusion GaussNewton Method in Industrial Environments
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DOI：10.1109/TII.2019.2909135.png)
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Abstract
En 中文
In a noisy manufacturing environment, range-based target localization for wireless sensor networks (WSNs) experiences various variations in range measurements, thus causing the unsatisfactory results. Starting from an empirical observation on the existing various industrial noise distribution, in this paper, a diffusion GaussNewton (GN) algorithm with cooperation strategy is proposed for solving target localization non linear-least-squares problem in a WSN. The proposed algorithm has an equalization effect on the unbalance noise distribution over the network by aggregating the global estimates into local GN update via diffusion strategy. When facing a hostile industrial environment where the ambient noise is heterogeneous or has the sudden changes across partial nodes, the significant performance degradation is produced by diffusion GN. To solve the problem, we propose further an improved version of diffusion GN, which is adaptive to sudden changes on noisy range measurements. Instead of using a static combiner, the new algorithm leverages the evolutionary game theory to assign a time-varying weight for the estimate from each neighboring node based on the individual range error. Consequently, the good estimates from the neighbors with high SNR have a larger weight in the combiner than the bad estimates caused by the low SNR or high noise. We also propose a simple but effective energy-accuracy tradeoff scheme by using a sigmoidal utility function. Some simulation examples show that the standard diffusion GN is effective in stationary noise and its improved version provides the adaptation to changing noisy environment. The effectiveness of energyaccuracy tradeoff is also validated.
Keywords:
Noise measurement
Wireless sensor networks
Peer-to-peer computing
Measurement uncertainty
Received signal strength indicator
Routing
Degradation
Diffusion strategy
distributed estimation
evolutionary game theory
Gauss-Newton (GN) method
nonlinear least squares
target localization
wireless sensor networks (WSNs)
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