A Wireless Fingerprint Location Method Based on Target Tracking

With the popularization of wireless networks, wireless positioning technology is used to locate the location of the target location. The rapid development of wireless location technology satisfies people's demand for positioning services. How to use existing equipment to improve positioning accuracy is particularly important. At present, most of the indoor positioning methods are based on the received signal strength fingerprint recognition algorithm. This algorithm establishing a fingerprint database of the location area signal strength, it matches the real-time collected signal strength. To achieve the purpose of location estimation. This paper first studies the accuracy of wireless fingerprint location using KNN classification algorithm and compares it with other positioning of fingerprint localization algorithms such as SVM, logistic regression and random forest. Finally, the target tracking algorithm is used to process the positioning result of the RSS based WIFI indoor positioning algorithm KNN in the indoor scene, and the trajectory analogy is given. The results show that compared with the traditional KNN algorithm, this method can effectively improve the positioning accuracy of about 20%.