科研之友
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摘要
Received signal strength indications (RSSI) received at multiple anchors decay with distances that the signals have traveled to reach the sensors, so the sensor of unknown node can be uniquely located. By converting the nonlinear equations into linear equations the unconstrained least square calibration (ULSC) and constrained least square calibration (CLSC) algorithms are all algebraic closed-form solutions for RSSI-based wireless localization. The designed ULSC and CLSC algorithms obtain the corresponding best linear unbiased estimator by considering the anchor position uncertainty. The simulations demonstrate the validity of the localization computation method and test the impacts of signal strength noises on localization error. The results also show that the localization error of CLSC algorithm is less than that of ULSC algorithm and more close to the position Cramer-Rao low bound (CRLB) which provides optimal position accuracy.
