Fundamental Limits of TOA/DOA and Inertial Measurement Unit-Based Wireless Capsule Endoscopy Hybrid Localization
In this paper, performance analysis of hybrid localization based on radio-frequency (RF) and inertial measurement unit (IMU) measurements for a single wireless capsule endoscopy (WCE) traveling the gastrointestinal tract is studied. Specifically, the multiple body-mounted sensors are considered which are located on the front and back of a patient’s medical jacket and form the uniform rectangular arrays (URAs). With the aim of locating the WCE, two types of RF measurements, namely time-of-arrival (TOA) and direction-of-arrival (DOA), are estimated from the received signals at the URAs transmitted by the WCE, which are integrated with the IMU acceleration measurements via the standard extended Kalman filter. Here, a posterior Cramér–Rao Bound (PCRB) of the proposed TOA/DOA and IMU-based hybrid localization is derived as fundamental limits on squared position error, where the accuracies of TOA and DOA measurements are entailed by means of CRB to account for their dependency on the environmental parameters, while the accuracies of the IMU measurements are addressed with the acceleration measurement error standard deviation. Numerical results are provided, sustained by simulations which verify the millimeter accuracy of the TOA/DOA and IMU-based hybrid localization within the regulation of medical implant communication services and the exactness of the PCRB.
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Related Subject Headings
- Networking & Telecommunications
- 4606 Distributed computing and systems software
- 4006 Communications engineering
- 1005 Communications Technologies
- 0906 Electrical and Electronic Engineering
- 0805 Distributed Computing
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Networking & Telecommunications
- 4606 Distributed computing and systems software
- 4006 Communications engineering
- 1005 Communications Technologies
- 0906 Electrical and Electronic Engineering
- 0805 Distributed Computing