雷达装备测试性设计优化技术

针对雷达装备测试性优化设计的实际技术需求，对雷达测试性优化设计过程进行了分析。以雷达装备各阶段数据为基础，综合考虑测试效能、测试代价、可靠性约束等要素，研究了基于测试代价和测试效能的测试性优化方法，并给出了基于最小测试代价的雷达系统测试性优化模型。针对模型多目标优化求解问题，给出了一种基于改进的粒子群优化算法。该算法引入混沌理论，使初始种群呈现多样性，避免了传统粒子群算法的早熟现象，同时提高了搜索的精度和速度。通过对案例的仿真与验证表明，利用这种改进的粒子群算法对基于最小测试代价的测试性优化模型进行求解时，能够在满足模型目标函数的约束条件下，获得全局最优解。

Optimizing technology of testability design for radar equipment

According to the actual technical requirements of radar equipment testability optimization design, the process of radar testability optimization design is analyzed. Based on the data of each stage of radar equipment and considering the factors of test efficiency, test cost and reliability constraint, the test optimization method based on test cost and test efficiency is studied, and the test optimization model of radar system based on minimum test cost is given. An improved particle swarm optimization algorithm is proposed to solve the multi-objective optimization problem. The chaos theory is introduced into the algorithm, which makes the initial population diversified, avoids the premature phenomenon of traditional particle swarm optimization, and improves the search accuracy and speed. Through the simulation and verification of the case, it is shown that this improved particle swarm optimization algorithm can obtain the global optimization model based on the minimum test cost under the constraints of the objective function of the model.