写出matlab形式的代码

要编写MATLAB代码来求解上述提出的三个问题，我们可以分别构建模型并编程实现。下面是每个问题的MATLAB代码概览：

### 问题 1 MATLAB代码框架
对于第一个问题，我们假设潜艇的中心位置在Z轴上的深度定位无误差，仅考虑X和Y轴方向的正态分布情况。我们需要找到一个方案最大化命中概率，并提供该概率的表达式。

function [maxProbability, optimalDepth] = problemOne(sigmaXY, submarineDimensions, warheadRadius)
    % submarineDimensions: [length, width, height]
    % warheadRadius: 杀伤半径
    
    % 初始化最优解
    maxProbability = 0;
    
    % 设置搜索定深引信引爆深度的空间
    depthRange = 150; % 已知潜艇中心位置的实际深度
    searchSpace = 150 - submarineDimensions(3)/2 : 1 : 150 + submarineDimensions(3);
    
    for depth = searchSpace
        % 计算当前引爆深度下的命中概率
        probability = calculateHitProbability(sigmaXY, submarineDimensions, warheadRadius, depth);
        
        if probability > maxProbability
            maxProbability = probability;
            optimalDepth = depth;
        end
    end
end

function prob = calculateHitProbability(sigmaXY, submarineDimensions, warheadRadius, detonationDepth)
    % 实现计算命中概率的具体算法
    % 提示：需结合潜艇尺寸以及深弹的引爆条件进行计算
end

### 问题 2 MATLAB代码框架
第二个问题是处理各个方向都有定位误差的情况，并寻找最佳引爆深度使命中概率最大化。

function [maxProbability, optimalDepth] = problemTwo(sigmaXY, sigmaZ, submarineDimensions, minSubmarineDepth, warheadRadius)
    % 初始化最优解
    maxProbability = 0;
    
    % 设置搜索空间
    searchSpace = minSubmarineDepth : 1 : submarineDimensions(3) + 150;
    
    for depth = searchSpace
        % 计算当前引爆深度下的命中概率
        probability = calculateHitProbabilityWithError(sigmaXY, sigmaZ, submarineDimensions, minSubmarineDepth, warheadRadius, depth);
        
        if probability > maxProbability
            maxProbability = probability;
            optimalDepth = depth;
        end
    end
end

function prob = calculateHitProbabilityWithError(sigmaXY, sigmaZ, submarineDimensions, minSubmarineDepth, warheadRadius, detonationDepth)
    % 实现包含定位误差情况下计算命中概率的具体算法
    % 提示：需要使用带误差的位置分布信息来评估命中可能性
end

### 问题 3 MATLAB代码框架
第三个问题中，我们需要规划多次投弹方案，以便使总命中概率达到最高。

function [maxTotalProbability, scheme] = problemThree(sigmaXY, sigmaZ, submarineDimensions, minSubmarineDepth, warheadRadius, numWarheads)
    % 初始化最优解
    maxTotalProbability = 0;
    
    % 设置搜索空间
    searchSpace = minSubmarineDepth : 1 : submarineDimensions(3) + 150;
    
    % 遍历可能的引爆深度组合
    for depth = searchSpace
        % 根据给定的引爆深度确定平面间隔
        gridSpacing = determineGridSpacing(sigmaXY, submarineDimensions, warheadRadius, depth, numWarheads);
        
        % 计算总体命中概率
        totalProbability = calculateTotalHitProbability(sigmaXY, sigmaZ, submarineDimensions, minSubmarineDepth, warheadRadius, depth, gridSpacing);
        
        if totalProbability > maxTotalProbability
            maxTotalProbability = totalProbability;
            scheme = struct('detonationDepth', depth, 'gridSpacing', gridSpacing);
        end
    end
end

function spacing = determineGridSpacing(sigmaXY, submarineDimensions, warheadRadius, detonationDepth, numWarheads)
    % 确定多个投弹间的理想平面间距
end

function prob = calculateTotalHitProbability(sigmaXY, sigmaZ, submarineDimensions, minSubmarineDepth, warheadRadius, detonationDepth, gridSpacing)
    % 实现多枚深弹投掷下计算总体命中概率的具体算法
    % 提示：考虑至少一枚深弹命中的逻辑
end

请注意以上提供的只是MATLAB函数的基本结构，具体实现细节如`calculateHitProbability()`等函数依赖于具体的数学模型定义。