Matrix computations (3rd ed.)
Statistical methods in surveying by trilateration
Computational Statistics & Data Analysis
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
The anatomy of a context-aware application
Wireless Networks - Selected Papers from Mobicom'99
Advanced Engineering Mathematics: Maple Computer Guide
Advanced Engineering Mathematics: Maple Computer Guide
An Introduction to Genetic Algorithms for Scientists and Engineers
An Introduction to Genetic Algorithms for Scientists and Engineers
Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
Advanced sensorial system for an acoustic LPS
Microprocessors & Microsystems
An efficient least-squares trilateration algorithm for mobile robot localization
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Revisiting trilateration for robot localization
IEEE Transactions on Robotics
Data association and tracking for automotive radar networks
IEEE Transactions on Intelligent Transportation Systems
Benefits of averaging lateration estimates obtained using overlapped subgroups of sensor data
Digital Signal Processing
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Trilateration is the most adopted external reference-based localization technique for mobile robots, given the correspondence of external references. The nonlinear least-squares trilateration formulation provides an optimal position estimate from a general number (greater than or equal to the dimension of the environment) of reference points and corresponding distance measurements. This paper presents a novel closed-form solution to the nonlinear least-squares trilateration problem. The performance of the proposed algorithm in dealing with erroneous inputs of reference points and distance measurements has been analyzed through representative examples. The proposed trilateration algorithm has low computational complexity, high operational robustness, and reduced systematic error and uncertainty in position estimation. The effectiveness of the proposed algorithm has been further verified through an experimental test.