Research On Adaptive Resource Management Technology For Phased Array Radar

The beam direction of the phased array antenna can switch in microseconds to hundreds of microseconds, which provides high agility of the phased array radar. At the same time, the phased array radar can change its working mode and parameters to adapt the dynamic external environment under the control of radar control computer. In order to make full use of the radar system, it is necessary to exert effective resource management to realize reasonable and dynamic resource allocation among the tasks.The time resource management, waveform management, time and energy resource combine management and radar dwell scheduling are studied. Firstly, starting from the maneuvering target tracking, the Interacting Multiple Model (IMM) tracking algorithm is introduced. In order to increase the tracking precision, the idea of multi-resolution is introduced in the traditional IMM algorithm, where multiple multi-rate models constitute the model set to realize interacting. A way of full rate tracking to a maneuvering target using multi-rate IMM algorithm is proposed.The time resource management of phased array radar is realized through adapting the update intervals of radar tasks. The adaptive update interval methods based on IMM algorithm is discussed. Several adaptive update interval algorithms based on fixed structure IMM are introduced, and a modified algorithm is proposed to overcome the shortage of recursive adaptive update interval method. The variable structure IMM algorithm settles the model choosing problem in the fixed structure IMM algorithm. According to the principle of variable structure IMM algorithm, an adaptive update interval algorithm based on adaptive grid IMM is proposed. A controllable parameter is introduced in both above algorithms. The balance between tracking precision and system load can be kept through adjusting the parameter, which shows the flexibility of corresponding algorithms. Furthermore, the idea of covariance control used to solve the sensor combination in centralized multi-sensor system is borrowed to realize the time resource management under multi-target environment. The multi-target time resource management algorithm based on IMM is given.As to the waveform management of phased array radar, two strategies based on IMM algorithm is studied, which are covariance matrix orthogonal and mutual information methods. The traditional covariance matrix orthogonal method is modified through taking the predicted covariance as target tracking covariance. Comparing the modified algorithm with the one based on mutual information, it is found that they provide similar speed tracking precision while the modified one has lower position tracking error. Based on the above work, the time resource and waveform combine management is realized through incorporating the adaptive update interval and waveform algorithms. In order to manage the time and energy resources at the same time, the width of transmitting pulse, the transmitting power and update interval are controlled together using the Quality-of-service based Resource Allocation Model (Q-RAM). The idea of service class is introduced to avoid frequent resource re-allocation caused by the dynamic system task load, and Q-RAM based on service class is obtained. It can decrease the resource re-allocation times effectively while provides similar system utility as basic Q-RAM method.The adaptive dwell scheduling algorithm is mainly studied in dwell scheduling strategies. The traditional adaptive dwell scheduling algorithm only considers the time resource constraint, while ignores the energy resource constraint. To this problem, the adaptive scheduling algorithms based on scheduling gain and online pulse interleaving are proposed. In the former algorithm, the model of scheduling problem is founded from the viewpoint of scheduling gain, which takes both time and energy resource constraints into consideration. The energy resource constraint is realized during the pulse interleaving process in the second algorithm. Both of them can decrease the task drop rate compared with the traditional scheduling algorithm, thus provide higher hit value ratio and time utility. Furthermore, according to the characteristics of signal processing in the Digtal Array Radar (DAR), an adaptive dwell scheduling algorithm for DAR is proposed through modifying the pulse interleaving method in conventional phased array radar, with which the DAR can schedule more tasks.