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Cooperative localization in wireless sensor networks

Cooperative localization in wireless sensor networks. IEEE SIGNAL PROCESSING MAGAZINE JULY 2005 Author: Neal Patwari, Joshua N. Ash, Spyros Kyperountas, Alfred O. Hero III, Randolph L. Moses, and Neiyer S. Correal. INTRODUCTION COOPERATIVE STATISTICAL MODELS LOCATION ESTIMATIONALGORITHMS

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Cooperative localization in wireless sensor networks

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  1. Cooperative localization in wireless sensor networks IEEE SIGNAL PROCESSING MAGAZINE JULY 2005 Author: Neal Patwari, Joshua N. Ash,Spyros Kyperountas,Alfred O. Hero III, Randolph L.Moses, andNeiyer S. Correal

  2. INTRODUCTION • COOPERATIVE • STATISTICAL MODELS • LOCATION ESTIMATIONALGORITHMS • COMPARISON • CONCLUSION

  3. INTRODUCTION • Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide varietyof applications. • we describe measurement-based statistical models useful to describe time-of-arrival (TOA), angle-of-arrival (AOA), and received-signal-strength (RSS) measurements in wireless sensor networks.

  4. INTRODUCTION • Using the models, we show how to calculate a Cramer-Rao bound (CRB) on the location estimation precision possible for a given setof measurements.

  5. Cooperative

  6. statistical models • TOA • 是利用收發站之間的時間差反推回兩站間的距離。 • RSS • 接收端所收到的訊號強度。 • AOA • 利用訊號接收時的角度去反推。

  7. Cramer-Rao bound (CRB) • CRB會產生一個下限值，這個值是極限，並不會在往下。 • 用來給TOA,RSS,AOA計算。

  8. LOCATION ESTIMATIONALGORITHMS • Centralizedalgorithms • Distributedalgorithms

  9. COMPARISON • Energy • 集中式訊息的跳數，會比分散式來的高。 • 混合式

  10. CONCLUSION • Cooperative localization research will continue to grow assensor networks are deployed in larger numbers and as applicationsbecome more varied. • We have presented measurement based statistical models of TOA, AOA, and RSS, and used them to generate localization performance bounds.

  11. 參考文獻 • 以可程式系統晶片發展平台實現無線網路室內定位之分析與應用 • 伽利略搜救信号FOA 和TOA 估计的克拉美-罗界

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