1 / 12

Cooperative localization in wireless sensor networks

Accurate and low-cost sensor localization is essential for wireless sensor networks. Measurement-based statistical models for TOA, AOA, and RSS measurements are discussed, including the calculation of Cramer-Rao bound for location estimation precision. Cooperative algorithms and comparison between centralized and distributed algorithms are presented, highlighting the impact on energy efficiency. The conclusion emphasizes the growing research in cooperative localization as sensor networks expand.

sjuanita
Download Presentation

Cooperative localization in wireless sensor networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related