Research And Simulation Of The Uav TDOA Location Technology For Target On The Surface Of The Earth

The time difference of arrival location technology is the research emphasis in the field of electronic intelligence reconnaissance. The time difference of arrival location based on the air can avoid the blind area problem based on the ground. Previous research of the TDOA based on the air aimed at the cooperation targets on the ground which emitted dense signals, and the research is lack of location non-cooperative targets. This paper takes unmanned aerial vehicle(uav) formation as the space-based platforms to locate the non-cooperative targets on the ground, and the main purpose is to research the TDOA technology locating the targets on the ground, which emit sparse signals. In this paper, the main research is:1) This paper sets up the signal propagation model between the target and uav airborne platform. The error of TDOA is mainly from the measure error of time of arrival and the time synchronization error of the platforms. This paper discusses the influence of the location precision from the relative velocity between UAV platforms and the target. According to the theory analysis, in a very short observation time, the influence of the relative velocity to the location precision is very small.2) This paper researches the time difference orientation technology of a single uav, and designs the time difference orientation solution of the short baseline case. The solution uses the VHF band reception antenna on the uav wings, gets the time difference of two arrival signals with generalized correlation algorithm, and determines the direction of the target with the size of the uav. This paper simulates the generalized correlation algorithm of signal and the orientation algorithm, and eliminates the fuzzy location positions, which is the basis of TDOA.3) This paper studies the time difference measurement technology using multi uavs, analyze the time synchronization methods. The research is mainly focus on the process algorithm of the time synchronization observation data, and puts forward the fast algorithm of the observation data. The main methods of time synchronization include common view method, all in view method and TWSTFT, and the application is according to the real occasion. Usually, the time synchronization observation data process algorithm is Vondrak data smoothing algorithm, but the data operation time is long. In this paper, Kalman smoothing algorithm is proposed for the time synchronization observation data process, and the comparison simulation can be found that the two results is almost same, but the time consuming of Kalman smoothing algorithm is shorter, which approves that Kalman smoothing algorithm can better adapt to the environment of multi uavs dynamic time synchronization.4) This paper studies time difference of arrival localization algorithm to the target on the earth’s surface, and puts forward the rapid position algorithm. This paper analyzes the earth coordinate system first, proposes the time difference of arrival location model to the target on the surface of the earth, and then analyzes the Newton iterative algorithm, proposes the analytical location algorithm, and finally proposes the important algorithm that is the Broyden fast location iterative algorithm. Based on the simulation and theoretical analysis of the three kinds of localization algorithm it can be found that the precision and computation amount between analytical location algorithm and Newton iterative algorithm is almost the same, but the calculation amount of Broyden fast location iterative algorithm is greatly smaller, which the location precision is under a reasonable error range. Generally, Broyden fast location iterative algorithm proposed in this paper can be able to locate the target on the ground faster.The uav time difference of arrival location technology to the target on the earth surface proposed in this paper is used in the specific research projects for a research institute, and it has the practical mean and the engineering background. This paper makes the simulation comparison of all the algorithms studied using the actual data, and verifies the correctness and practicability of the algorithms.