MATLAB 实现动态规划算法进行雷达干扰资源分配 - 代码示例和详解

以下是用 MATLAB 实现动态规划算法进行雷达干扰资源分配的示例代码：\n\nMATLAB\nfunction [optimalAllocation, maxScore] = radarAllocation(distances, scores, interferenceThreshold)\n numTargets = length(distances);\n numInterference = size(interferenceThreshold, 2);\n \n % 初始化动态规划矩阵\n dpMatrix = zeros(numTargets, numInterference + 1);\n \n % 动态规划计算\n for i = 1:numTargets\n for j = 1:numInterference + 1\n if j == 1\n % 没有干扰资源的情况\n dpMatrix(i, j) = max(dpMatrix(i-1, j), scores(i));\n else\n % 有干扰资源的情况\n interferenceUsed = 0;\n for k = 1:numTargets\n if distances(i, k) <= interferenceThreshold(i, j-1)\n interferenceUsed = interferenceUsed + dpMatrix(k, j-1);\n end\n end\n dpMatrix(i, j) = max(dpMatrix(i-1, j), scores(i) + interferenceUsed);\n end\n end\n end\n \n % 获取最优分配方案和最大得分\n optimalAllocation = zeros(numTargets, 1);\n maxScore = dpMatrix(numTargets, numInterference + 1);\n for i = numTargets:-1:1\n if maxScore == dpMatrix(i-1, numInterference + 1)\n optimalAllocation(i) = 0;\n else\n optimalAllocation(i) = 1;\n maxScore = maxScore - scores(i);\n end\n end\nend\n\n\n使用示例：\n\nMATLAB\n% 输入雷达与目标之间的距离\ndistances = [5, 10, 15, 20];\n\n% 输入每个目标的评分\nscores = [10, 15, 20, 25];\n\n% 输入每个目标的干扰资源阈值\ninterferenceThreshold = [8, 12, 18, 22; 7, 11, 17, 21; 6, 10, 16, 20; 5, 9, 15, 19];\n\n% 输入干扰资源的数量\nnumInterference = size(interferenceThreshold, 2);\n\n% 调用函数进行雷达干扰资源分配\n[optimalAllocation, maxScore] = radarAllocation(distances, scores, interferenceThreshold);\n\n% 输出最优分配方案和最大得分\nfprintf('最优分配方案：%s\n', mat2str(optimalAllocation));\nfprintf('最大得分：%d\n', maxScore);\n\n\n请注意，输入的距离矩阵 distances 需要是一个对称矩阵，表示雷达与目标之间的距离。干扰资源阈值矩阵 interferenceThreshold 是一个 numTargets x numInterference 的矩阵，表示每个目标在每个干扰资源上的阈值。最终输出的最优分配方案 optimalAllocation 是一个 numTargets x 1 的向量，其中 1 表示分配了干扰资源，0 表示没有分配干扰资源。最大得分 maxScore 表示在给定干扰资源约束下所能达到的最大得分。