Theory And Method Of Resource Optimization And Management For Phased Array Radars

As a multi-function and high-performance radar system, phased array radar has the advantages of flexible beam pointing direction, versatile waveforms, controllable system parameters, as well as the effective resource allocation strategy and powerful data processing capacity. It is playing an important role in the future advanced radar systems. All the aforementioned predominance depends on the effective resource management. Resource management technique for phased array radar aims at improving the radar system performance by effectively task scheduling, resource allocation and parameter control. It is a combination of radar technique, computer technique and control technique. Thereby resource management technique has been a key factor in modern phased array radar system.This dissertation studied some general theory and technique in phased array radar resource management, including search resource management, multi-target tracking management, radar task scheduling, observation mission planning, real-time load allocation and task planning system design for space surveillance phased array radar.Parameter optimization and search strategy design for phased array radar search mode was firstly studied in the dissertation. Based on the analysis of search time, pulse integration number and detection performance, the optimum search parameter was obtained for the detection of single dwell time. While for the multi-frame integration cases, the impact of search resource on the radar system detection performance was discussed and the optimum search model with limited search resources was derived. Furthermore an optimum strategy of parameter adjustment was proposed. Based on the principle of the maximal information gain, a cued search method of phased array radar was presented, along with the discussion on the calculation of cued search region, beam position arrangement and the estimation of priori probability distribution.According to the concept of covariance control, the theoretic architecture of multi-target tracking resource management for phased array radar was presented. And an optimum resource management model was built, together with a multi-target tacking resource management algorithm. Extending to the steady state tracking and maneuvering target tracking, two resource management algorithms were proposed based on the Riccati equation and IMM(Interacting Multiple Model) filter respectively. Furthermore a joint adaptive scheduling algorithm of beam and waveform was presented for time-energy resource management in phased array radar system.With the analysis of the real-time task integrated priority by multi-attribute parameters, a real-time task modified EDF(Earliest Deadline First) scheduling model for phased array radar was built. The real-time task model and an adaptive real-time task scheduling algorithm for phased array radar were proposed. The schedulability condition was analyzed, followed by an effective task adjustment method under the condition of system overload. For the space surveillance phased array radar system, an observation mission planning algorithm was proposed. Furthermore, based on the task model of changeable observation span, an adaptive mission planning algorithm was presented which can evidently improve system performance.Subsequently, by introducing divisible load theory to real-time task processing, an optimum real-time divisible load allocation model was established for phased array radar. Aiming at the heterogeneous bus network of radar system, the real-time divisible load allocation method was studied, and the optimum load distribution sequence as well as the processor number was given. Then the parameter estimation for the bus network was discussed.Finally, for the space surveillance phased array radar system, the design and realization of task planning subsystem was studied. The basic principle and function requirement for designing the task planning subsystem were given. Then processing flow and module structure were presented. Based on the above work, a general task planning software was achieved.