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A new algorithm is proposed for phased array radar search function resource allocation. The proposed algo- rithm adaptively priorities radar search regions and in overload situations, based on available resources, radar characteristics, maximum range and search regions, optimally allocates radar resources in order to maximize probability of detection. The performance of new algorithm is evaluated by the multifunction phased array radar simulation test bed. This simulation test bed provides capability to design and evaluate the performance of different radar resource management, target tracking and beam forming algorithms. Some results are presented that show capabilities of this simulation software for multifunction radar algorithms design and performance evaluation. Keywords—Phased array radar, radar resource allocation, radar modeling, radar simulation, radar performance evaluation. proposed algorithm is able to allocate radar resources in order to maximize probability of detection based on available search load and adaptive prioritization of search regions. In other words it decides between decrease of useful detection range and exclusion of some search regions. Performance of the pro- posed algorithm is evaluated by Multi Function Array Radar Simulation Test Bed (MFARSTB) initially presented in (1). MFARSTB is a tool for MFAR designers. In the MFARSTB, active phased array radar is considered as a pilot for different radar resource management, target tracking and beam forming algorithms development and comparison. In this simulation test bed, transmitting and receiving chain, antenna structure and signal processing algorithms are fixed. User may write his or her own radar resource management, target tracking and beam forming algorithms and after defining appropriate operational scenarios, asses results of the designed algorithms on the radar performance. This is necessary because these different data association, tracking and radar management algorithms should be designed in relation to each other and the interactions between them should be considered in the design stage. Organization of the paper is as follows: In section II adaptive prioritization of search regions is presented. In section III radar search function optimization algorithm in overload situations is illustrated. Section IV describes the simulator architecture and capabilities, models of radar subsections and received signal modeling. In section V some simulation results are presented which show performance of the new algorithm and capabilities of MFARSTB in the development and perfor- mance evaluation of different MFAR algorithms.

A New Algorithm for Phased Array Radar Search Function Improvement in Overload Situations