Abstract
In localization systems based on the emission of reference radio signals, an important issue related to the reliability of sensor operation is the problem of operating time and power of the emitted reference radio signal. There are many localization methods that have proven useful in practice and that use a reference radio signal for this purpose. In the issue of determining the location of radio emitters, various radio signal propagation models are used to determine the effective range and distance of the sensor-receiver from the radio emitter. This paper presents an adaptive power control algorithm for a transmitter, as a reference emitter, operating in power-saving mode. An important advantage of the presented solution is the adjustment of the localization system accuracy at the assumed level of energy radiated by radio emitters based on the RSSI signal received power estimation.
Highlights
Algorithm for an received signal strength indicator (RSSI)-BasedThere are many publications on localization using the RSSI method and a fusion of localization methods, including RSSI, enabling the localization of moving radio effectors, e.g., indoors
The very problem of the error caused by the RSSI, which affects the accuracy of position estimation, is often the subject of publications on in-depth analyses [5], attempts to correct and predict this error [6], and the synthesis of new optimal location algorithms [7,8,9,10] including the use of neural networks [11,12]
According to the authors of [12], the system consisting of 13 radio sensors connected to a neural network with the proposed structure shows the high accuracy of position estimation (97.92% with an error of 2.8%) of a human moving in a complex office environment, without the need to perform complicated calibration
Summary
There are many publications on localization using the RSSI (received signal strength indicator) method and a fusion of localization methods, including RSSI, enabling the localization of moving radio effectors, e.g., indoors. The very problem of the error caused by the RSSI, which affects the accuracy of position estimation, is often the subject of publications on in-depth analyses [5], attempts to correct and predict this error [6], and the synthesis of new optimal location algorithms [7,8,9,10] including the use of neural networks [11,12]. During the scientific research preceding the study described in the paper, there was no explicitly described algorithm for the automatic control of the transmitter power operating on the qualitative indicator—error of distance estimation—enabling a compromise between energy consumption and position estimation error depending on the assumed work scenario of the mobile radio effector. In this paper, it was decided to explain the influence of transmitter power on the accuracy of distance estimation in the RSSI method and propose a simple ATPC algorithm containing sensor feedback
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