Matching Location Technology Research Based On The Characteristics Of Ray-tracing

With the fast development of mobile communication system in recent years, the indoor wireless location technology is gradually becoming a research highlight. It is applied in the various circumstances including station, hospital, airport, mall, museums and so on, and its outcome is used for handling with emergency such as leading, guidance, fire prevention and counter-terrorism.The location technology based on base stations and mobile equipments cannot work in the indoor environment because of the Non-Line-of-sight (NLOS) propagation. The different architectural concept, style, structure, size or display brings out the NLOS propagation which is the key factor to limit this kind of location technology. The location technology based on signal map is one of major ways to cope with the NLOS propagation.After a number of researches on the sequence location algorithm based on ray-tracing, the sequence of ray-tracing location algorithm based on wavelet de-noising is presented. The de-noising threshold based on wavelet transform is utilized for eliminating the noise from the impulse response of the target, and then the impulse response compares with the ones of position-known beacons which are pre-built by the ray-tracing technology to estimate user location. The simulation demonstrates that the algorithm has a high success rates to locate users'positions, and reduces the impact of the noise effectively.After the analysis of the existing city and indoor location technologies based on signal map, this paper further puts forward a ray-tracing location algorithm related with channel feature extraction and matching based on wavelet transform. This algorithm first obtains the multi-path signals from the receiver reversely and calculates their impulse response using the ray-tracing method, which simplifies the work comparing with the realistic measurements modeling. Then we extract the feature of the channel from the wavelet transform coefficient matrix of the discrete impulse response sequence. The feature of the channel not only contains the information of how much signal strength decline, but also when the decline happens. It is more complete than the signal strength sequence. In order to build the signal map conveniently and reduce the complication of the matching algorithm, the singular value vector extracted from the wavelet coefficient matrix by singular value decomposition is used as the feature of the signal site. Computer simulation shows that the character of location calculated from the algorithm has excellent stabilization. The location results demonstrate the ability of our algorithm to estimate user location with a higher degree of the accuracy than the algorithm that uses the receive signal strength as the characteristic of the signal map. The overall accuracy of locating objects satisfies the need of the inside location service, and the performance becomes better as the beacon density increases.