Indoor positioning method based on steepest descent method

Abstract

The invention discloses an indoor positioning method based on a steepest descent method. The indoor positioning method is applied to positioning of indoor unknown nodes, position evaluation of the unknown nodes is carried out based on a signal intensity (RSSI) distance measurement method, optimization evaluation is carried out for the result through employing an optimization method to acquire the smallest-error position result. According to the method, under the condition of a lognormal shadow model, a reception signal intensity value is detected, influence of multiple factors onto an RSSI value is considered, a five-point quadratic curve fitting average method is employed, weight is carried out to correct the RSSI value, a least square method is utilized to correct a distance, the blind node position can be solved through a three-edge positioning algorithm, and the steepest descent method of the optimization method is employed to solve the accurate position of blind nodes. The method is advantaged in that indoor positioning precision is improved, and a positioning error is reduced.

Description

technical field [0001] The invention relates to an indoor positioning method based on the steepest descent method, which belongs to the technical field of communication. Background technique [0002] Indoor positioning technology refers to the realization of position positioning in the indoor environment. It mainly uses wireless communication, base station positioning and other technologies to integrate a set of indoor position positioning system, so as to realize the position monitoring of people and objects in the indoor space. Common indoor wireless positioning technologies include Wi-Fi, Bluetooth, infrared, ultra-wideband, RFID, ZigBee and ultrasonic technologies, and the present invention uses the positioning technology of wireless sensor networks. Indoor positioning technology based on wireless sensor network has the characteristics of low sensor node cost, low power consumption, easy networking data transmission and so on. The realization of the wireless sensor netw...

AI Technical Summary

Problems solved by technology

[0004] The existing N-Hop Multilateration Primitive algorithm has inaccurate positioning and limited use, and each algorithm has different requirements for sensor nodes depending on the application. Later generations based on the existing node positioning algorithm, For its analysis and comparison, the positioning algorithm expressed in the form of the product of the average distance per hop and the number of hops between nodes is adopted. This algorithm is simple to calculate, not only realizes accurate positioning of nodes, but more importantly, omits other redundant information of nodes

The current wireless sensor network positioning algorithm uses the combination of centroid and RSSI, extracts the advantages of the two, and integrates them, which reduces the computational complexity of the RSSI method and improves the position accuracy of the centroid algorithm. However, if in a complex channel model , the error of its centroid algorithm is relatively large

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