Research On Ground Target Positioning Technology Based On TDOA

It is very important to realize the accurate positioning of the target,whether it is the countermeasure of modern electronic information or the protection of the target.With the development of society and the increase of people’s demand,there are higher and higher requirements for the accuracy of wireless positioning.Passive time difference positioning is widely used for its advantages of strong concealment,high positioning accuracy and low erection difficulty.However,the accuracy of the monitoring system,the interference in the environment,the number and layout of the monitoring stations and the calculation algorithm used will affect the final positioning effect.Therefore,thesis focuses on several aspects of improving positioning accuracy.Thesis first introduces several different kinds of wireless location methods.After comparing the advantages and disadvantages of these methods,the time difference positioning technique is chosen as the research basis.Thesis analyzes the key factors affecting the time difference location and deduces the mathematical model and several classical algorithms.The results of Chan algorithm and Taylor series expansion algorithm are analyzed by using RMSE as the standard to evaluate the positioning accuracy.Then the errors caused by non-line-of-sight propagation and multipath effect are analyzed and the error models in different environments are derived.With the addition of environmental errors,the classical algorithm is simulated and analyzed again to observe the impact of environmental errors on positioning results,and the method of correcting the measured value by Kalman filter algorithm is studied to reduce the measurement error.On this basis,an improved Kalman filter is proposed for the large errors that occur suddenly and the implementation process of the improved algorithm.The measured value is further modified by an improved Kalman filter algorithm.Experimental results show that the improved filtering algorithm can reduce the positioning error more effectively.Finally,the influence of the number and layout of monitoring stations on positioning performance in the positioning area is studied,and the influence of the number,height and distance of different monitoring stations on positioning is analyzed,and the range of stations with good positioning effect is obtained.The positioning effect under several regular layout methods is simulated and analyzed.Then,the optimal layout scheme of the monitoring station is studied,and the optimal layout mode within the range of the distribution station is solved by the optimization property of the genetic algorithm.The simulated annealing algorithm is used to improve the genetic algorithm,and the local optimization ability of the algorithm is improved to solve the better distribution mode.Experimental results show that the optimization algorithm can find a better arrangement of monitoring stations through iteration.