Abstract:
The demands for high localization accuracy in wireless sensor networks (WSNs) have led to the development of various innovative algorithms. This article proposes a distri...Show MoreMetadata
Abstract:
The demands for high localization accuracy in wireless sensor networks (WSNs) have led to the development of various innovative algorithms. This article proposes a distributed joint robust filter (DJRF) algorithm for addressing fluctuant localization errors caused by the measurement noises and ill-conditioned matrix solution. Firstly, the distributed solution is established after considering the non-Gaussian noises, drifted anchor node coordinates as well as unknown point-to-point distances. Secondly, since the outliers may seriously degrade the localization performance, the robustness filter integrated with virtual observation is used to estimate the point-to-point distances. Thirdly, the variable separation method that can weaken the influence of ill-conditioned matrices is proposed for mobile target localization without generating large errors. The numerical results show that the proposed DJRF combines the merits of distributed solution and robustness filter, which effectively deal with various uncertainties under an acceptable amount of computation. Furthermore, the DJRF experimental result has a 0.26 m average error under non-Gaussian noises and increases to a 0.33 m average error in a more actual scenario. The DJRF algorithm uses outlier elimination and a robust filter to suppress its divergent trend, which can further verify the superiority compared with relevant localization algorithms.
Published in: IEEE Transactions on Instrumentation and Measurement ( Volume: 71)
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- IEEE Keywords
- Index Terms
- Target Location ,
- non-Gaussian Noise ,
- Robust Filter ,
- Large Errors ,
- Average Error ,
- Localization Accuracy ,
- Localization Performance ,
- Localization Error ,
- Local Algorithm ,
- Wireless Sensor Networks ,
- Actual Scenario ,
- Nodal Coordinates ,
- Innovative Algorithm ,
- Ill-conditioned Matrix ,
- Covariance Matrix ,
- Error Variance ,
- Linear Approximation ,
- Base Station ,
- Solution Process ,
- Radio Waves ,
- Time Difference Of Arrival ,
- Mobile Nodes ,
- Error Accumulation ,
- Extended Kalman Filter ,
- Unscented Kalman Filter ,
- Received Signal Strength Indicator ,
- Average Localization Error ,
- Filter For Estimation ,
- Deployment Strategies ,
- Coordinate Error
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Target Location ,
- non-Gaussian Noise ,
- Robust Filter ,
- Large Errors ,
- Average Error ,
- Localization Accuracy ,
- Localization Performance ,
- Localization Error ,
- Local Algorithm ,
- Wireless Sensor Networks ,
- Actual Scenario ,
- Nodal Coordinates ,
- Innovative Algorithm ,
- Ill-conditioned Matrix ,
- Covariance Matrix ,
- Error Variance ,
- Linear Approximation ,
- Base Station ,
- Solution Process ,
- Radio Waves ,
- Time Difference Of Arrival ,
- Mobile Nodes ,
- Error Accumulation ,
- Extended Kalman Filter ,
- Unscented Kalman Filter ,
- Received Signal Strength Indicator ,
- Average Localization Error ,
- Filter For Estimation ,
- Deployment Strategies ,
- Coordinate Error
- Author Keywords