多目标数据关联算法MATLAB实现

多目标数据关联算法MATLAB实现（NNDA/PDA/JPDA/IMM）

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一、核心

1. 最近邻数据关联（NNDA）

function [assignments] = nnda(observations, tracks, threshold)
    % 输入: observations - 检测量测矩阵 (N×4)
    %       tracks - 现有航迹 (M×4)
    %       threshold - 门限距离
    % 输出: 关联矩阵 (M×N)
    
    N = size(observations,1);
    M = size(tracks,1);
    cost_matrix = zeros(M,N);
    
    for i = 1:M
        for j = 1:N
            % 马氏距离计算
            delta = observations(j,:) - tracks(i,1:3);
            S = tracks(i,4:6); % 协方差矩阵
            cost_matrix(i,j) = sqrt(delta*S*delta');
        end
    end
    
    % 关联决策
    assignments = zeros(M,N);
    for i = 1:M
        [~,idx] = min(cost_matrix(i,:));
        if cost_matrix(i,idx) < threshold
            assignments(i,idx) = 1;
        end
    end
end

2. 概率数据关联（PDA）

function [assignments] = pda(observations, tracks, clutter_density)
    % 输入参数:
    % clutter_density - 杂波密度 (次/平方公里)
    % 其他参数同上
    
    [M,N] = size(observations);
    cost_matrix = z