使用星凸随机超曲面模型对扩展对象和分组目标进行形状跟踪（Matlab代码实现）

💂♨️👨‍🎓Matlab代码👨‍🎓♨️💂

function randomHypersurfaceModel_2011(numberOfMeasurement)
if nargin ==0
numberOfMeasurement= 100;
end
% Number of Fourier coefficients
nr_Fourier_coeff = 11;
% State describtion prior [b0--bn, x, y]
x = zeros(nr_Fourier_coeff + 2, 1);
x(1) = 1.5;
% State covariance prior
C_x = diag([ones(1, nr_Fourier_coeff).*0.02, 0.3, 0.3]);
% Measurement noise
measurementNoise = diag([0.2, 0.2].^2);
% Scale properties
scale.mean = 0.7;
scale.variance = 0.08;
% Angular resolution for plotting
phi_vec = [0:0.01:2*pi];
% Object size
a = 3;      % -- width of the horizontal rectangle
b = 0.5;    % | height of the horizontal rectangle
c = 2;      % | height of the vertical rectangle
d = 0.5;    % -- width of the vertical rectangle
sizeObject = [a b c d];
% Object shape bounds
objectBounds = [[-d, -c];[d, -c];[d, -b];[a, -b];[a, b];[d, b];[d, c];
[-d, c];[-d, b];[-a, b];[-a, -b];[-d, -b]]' ./ 2;
% Main
% Plot
h_object = fill(objectBounds(1, :), objectBounds(2, :), [.7 .7 .7]);
hold on
xlim([-3 3]);
ylim([-3 3]);
axis equal
xlabel('x-Axis')
ylabel('y-Axis')
title('Random Hypersurface Model Simulation')
for j = 1 : numberOfMeasurement
% Get new measurement
newMeasurement = getNewMeasurement(sizeObject, measurementNoise);
% Filter step
[x, C_x] = UKF_FilterStep(x, C_x, newMeasurement, [scale.mean; [0 0]'], ...
blkdiag(scale.variance, measurementNoise), @f_meas_pseudo_squared, nr_Fourier_coeff);
% Plot
shape = calcShape(phi_vec, x, nr_Fourier_coeff);
h_measure = plot(newMeasurement(1), newMeasurement(2), '+');
h_shape =  plot(shape(1, :), shape(2, :), 'g-', 'linewidth', 2);
legend([h_object, h_measure, h_shape],'Target', 'Measurement', 'Estimated shape')
drawnow;
if j ~= numberOfMeasurement
delete(h_shape)
end
end

📜📢🌈参考文献🌈📢📜

[1]李永永,王莉.星凸形随机超曲面粒子扩展目标跟踪滤波器[J].舰船电子工程,2022,42(06):42-46+75.

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