Research on Indoor Positioning Algorithm Based on SAGA-BP Neural Network
نویسندگان
چکیده
The Indoor positioning based on the ZigBee received signal strength index has attracted more and researchers’ attention and, due to its low cost, hardware power consumption easy implementation. However, because of multipath effects shadow effects, traditional indoor algorithms cannot obtain good effects. In order improve accuracy positioning, this paper proposes an algorithm annealing (SA) genetic (GA) optimized neural network (SAGA-BP), superiority is proved through simulation experiment. First, establish position relationship between indicator(RSSI) target position, arrange node structure model collect signals a fingerprint database. Then use mechanism combined with optimize initial weight threshold algorithm, so that it can quickly jump out local optimal solution achieve high-precision positioning. Experiments have effectiveness algorithm. Compared BP GA-BP algorithms, SAGA-BP average error 0.75m for RSSI after acquisition processing, 1.24m. 0.98m. Thus, higher accuracy.
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ژورنال
عنوان ژورنال: IEEE Sensors Journal
سال: 2022
ISSN: ['1558-1748', '1530-437X']
DOI: https://doi.org/10.1109/jsen.2021.3120882