Research On Radar Resource Management And Target Tracking Algorithm

Radar is an essential high-tech equipment in the modern information battlefield and it’s moving towards adaptation and multifunction with the development of stealth technology and the increasingly hostile environment. Radar resource management is a means to improve the performance of radar whose essence is the valid configuration of radar task parameters. In this way, the purpose of saving system resource and making full use of system performance can be achieved. Radar resource management includes searching tasks management, tracking tasks management and beam dwell scheduling. The resource management under the tracking module mainly refers to the time resource management by the control of the sampling period and energy resource management by the control of the parameters related to the transmitting waveform. The system parameters get optimum configuration on the guarantee of tracking accuracy at last.The radar resource management under the tracking module is researched in this paper. Firstly, starting from the target tracking algorithm, the three basic target tracking algorithms, namely, the Kalman filtering, ? ?? filtering, ? ?? ?? filtering are introduced. And then the three maneuvering target tracking algorithms, namely, the Current Statistics Model(CSM) filtering, adaptive ? ?? filtering, Interacting Multiple Model(IMM) filtering are also put forward in this paper. The performance of three maneuvering target tracking algorithms, including tracking accuracy and time consumption, is evaluated. Simulation results verify that the IMM filtering has better tracking accuracy while the CSM filtering has better real time.Secondly, three resource management algorithms based on adaptive target tracking for phased array radar are researched which are all realized through CSM algorithm. The predictive covariance and predictive estimation error covariance are controlled by the threshold and expected tracking accuracy under the spherical coordinates respectively to realize the adaptive change of update intervals and number of pulse repetition in the first two algorithms in which time resource and energy resource have been managed. The third algorithm, which makes both the update interval and the number of pulse repetition change adaptively, is the combination of the first two algorithms. The simulation validates the effectiveness of the three methods and the advantage of the complete parameters adaptive control.Finally, combined with the radar Radio Frequency(RF) stealth technology, tracking resource has been managed for a new style radar system which has MIMO(Multiple Input Multiple Output) detection mode. Expression of intercept factor for MIMO radar is derived from the concept of traditional radar intercept factor, which has been the objective function to optimize the performance of radar RF stealth. Another part of the optimization model is the constraint which relates to the predictive covariance and echo signal-to-noise ratio. The subarray division number, average transmission power, beam dwell time and sampling period are the optimized parameters in this model. The solution to the model by applying genetic algorithm suggests that with the proposed target tracking algorithm MIMO radar can offer better RF performance and tracking precision.