Study Of Keyless System Localization Algorithm

Keyless System is not only a new symbol in automotive electronics, but also aninevitable development tendency in Vehicle Anti-theft technology. The key position detectiontechnology built upon Wireless Location is one of the pivotal technologies in Keyless System.The research for location algorithm of Keyless System concerns whether the electronicsystem can achieve intelligent control of the vehicle, and related to vehicle electronic systemsecurity. It also contributes to the study of Wireless Sensor Network at the same time.The Wireless Location Algorithm based on RSSI(Received signal strength indicator)technology, will use the Signal attenuation model to transform the receiving signal strengthinto the distance, thereby to realize locating. It is the mainstream of Wireless Locationtechnology currently, which has low power consumption, low hardware requirements and lowcost. This paper is carried out by analyzing Wireless Location technology and basic theory ofKeyless System. By comparing the summary of the research, this paper adopted the locationalgorithm based on RSSI. Under the further understanding of the electromagnetic wavepropagation theory, this paper uses the transmission line theory to calculate the433MHZsignal transmission and reflection energy ratio on the car seat, andbuilds a433MHZ signal attenuation model in the vehicle environment, then comparesthis attenuation model and the model of free space by simulation. The measured observationproves the validity of this model.Since the Wireless Location algorithm based on distance measurement exist thecumulative error during the process of position calculation, it is very necessary to reduce thecumulative error after solving the problem of the validity of the model. This essay utilizes theleast squares method to obtain the conclusion that the coefficient matrix impacts the accuracyof positioning, then optimizes the matrix and improves the accuracy of the calculation.Considering the RSS values are affected by environmental factors, it may be unstable anddeclinational. Taking a variety of constraints in the algorithm into account, the apparent biasvalues are filtered to ensure the data reality to some extent. Twice-weighted factor isintroduced to overcome the inadequate utilization of weighted centroid algorithm data.A second weighted is conducted in order to estimate a second position and make a further amendment of the locating result, then the positioning accuracy reaches the establishedrequirements.At last, the algorithm in this paper and Weighted Centroid Algorithm as well as leastsquare method are simulated and compared in the MATLAB platform. The simulating resultshows that the utilization of data in this improved algorithm is higher, with better positioningaccuracy and smaller position error rate in the interior of vehicle environment.