Research Of TOA&DOA Joint Estimation Methods In Wireless Position System

Position location is a technique that determines the position of a mobile device, often in conjunction with some additional mapping or direction information, in a wireless communication system. It has been widely applied in military and civil fields. Position location and navigation system include: radar, TACAN, Loran C,VORTAC,JTIDS,GPS.There are numerous possible applications for location services in a wireless network system. Examples of such applications span from information services, such as weather notifications and traffic reports, to more important assistance services such as safety and security. In fact, locating 911 wireless phone callers (E911) has become mandatory in North America, the Federal Communications Commission (FCC) issued a Report and Order in October 1996 requiring that wireless network operators, such as cellular and personal communications service (PCS) carriers, implement an E-911 location capability by October 2001.Wireless network operators connecting to the public switched telephone network must implement E-911 service in two phases: Phase I stipulates that the system must pass the caller's phone number, cell-site, and cell-sector location information through to a responsible public safety answering point (PSAP). Carriers were to complete this step by April 1998. Phase II presents the more challenging task,at least from a location technology standpoint, of providing the 911 caller's location to the appropriate PSAP with an accuracy of 125 meters root-mean-square (RMS) in at least 67 percent of all cases.The details have subsequently been subject to debate,but this initial requirement gives an indication of the expected accuracy. The location systems developed for the E-911 requirement have been widely regarded as an enabling technology for location-based services;Location-based services generally require high location accuracy in order to have acceptable performance in the market. As a result, the demand for high performance and cost effective position location technologies is increasing. Detecting the time and angle of the signal arrival via the direct path between a mobile transmitter and base station receiver is the most important basis for the majority of technologies developed for location-based services. A precise time and direction of arrival measurement results in a more accurate location estimate. Regardless of the wireless system deployed, the performance of a location technology depends on accuracy, consistency, reliability, and the speed of themeasurements of time and angle of signal arrivals.In this paper, we have analyzed all the methods of TOA,DOA,TOA&DOA joint estimation, and compared them in the accuracy of position. Although TOA&DOA joint estimation is more complex, it's more accuracy and will lead the future.Then work content:Chapter one: we have introduced the background of wireless network location briefly and summed up various kinds of position technology exist. Among them Sequential Monte Carlo method, which is known as particle filter attracts our eyes. The more non-linear ,or the more non-Gaussian noise, the more potential particle filters have, rather cheap and the sampling rate slow.Chapter two: we have introduced the basic concepts of the sensor array signal processing method and linesr sensor array models, and linear sensor array is used in the simulation of this paper.Chapter three: we have analyzed the basic theories of parameter estimation, with respect to DOA, TOA and joint:About DOA: we have introduced some of the common estimation methods, and detailed in sub-space method. Because the standard MUSIC data model has some mismatches with the practice, we have made some modifications, and the simulation later shows the improvement in the accuracy. Followed with two kinds of simulation which are MUSIC and ESPRIT.About TOA: we have introduced some of the basic methods, and detailed in Time-frequency estimation method and MUSIC, and later are the simulations respected to the each method.About DOA/TOA: In this we mainly introduced the Maximun-likehood method, and applied it in the DOA/TOA joint estimation simulation. We also have done the simulation in MUSIC method.Chapter four: In This chapter, we made a joint estimation of the parameter of AOA and TOA location on termination in mobile communication net. In a parametric multi-path propagation model, source is received by an antenna array via wireless channels, each described by an arrival angle, a delay, and fading parameter. What's more, it is often relevant to estimate the directions and relative delays of each multi-path ray. We will derive a close-form subspace-based method for the simultaneous estimation of these parameters from an estimated channel impulse response, using knowledge of the transmitted pulse shape function.The algorithm uses a two-dimensional (2-D) ESPRIT—like shift—invariaxne technique to separate and estimate the phase shifts due to delay and direction of incidence with automatic pairing of the two parameter sets* by that way we can also prevent the effect of the noise. Finally, in the presence of noise, wt will stimulate the algorithm and analysis the effect of the noise power on the result of the compute stimulation.Chapter five: Considering the potential of Sequential Monte Carlo method, we summed up the Bayesian Method ,and detailed in the Particle Filter. Later we have constructed a model of TOA&DOA joint estimation using particle filter, and the simulation shows it's availability.Finally, we make conclusions for completed work and main contributions of this research work, and prospect for directions of future research.