1) Figure 창 on/off 토글 추가

2) Coverage 분석 도구 추가 - 추가 검증 필요

05. Performance Analysis/analyze_coverage.m

@@ -0,0 +1,324 @@
+function [snr_coverage_2d, azimuth_deg, elevation_deg, coverage_info, fig] = analyze_coverage(RadarParams, target_range_m, target_rcs_dBsm)
+    % Coverage 분석: 2D 안테나 패턴 기반 각도별 SNR 계산
+    % 
+    % 방법:
+    % 1) Azimuth 0도, Elevation 0도에서 기준 SNR 계산
+    % 2) 다른 각도의 상대 이득 차이로 SNR 계산 (효율적)
+    % 3) 입력한 RCS 값 반영
+    %
+    % 입력:
+    %   - RadarParams: 레이더 파라미터 구조체
+    %   - target_range_m: 표적 거리 (m), 기본값 100
+    %   - target_rcs_dBsm: 표적 RCS (dBsm), 기본값 0
+    %
+    % 출력:
+    %   - snr_coverage_2d: 2D SNR 맵 [elevation x azimuth]
+    %   - azimuth_deg: 방위각 벡터
+    %   - elevation_deg: 고각 벡터
+    %   - coverage_info: 커버리지 정보 구조체
+    %   - fig: 생성된 figure 핸들
+    
+    %% 입력 파라미터 처리
+    if nargin < 2
+        target_range_m = 100;  % 기본: 100m
+    end
+    if nargin < 3
+        target_rcs_dBsm = 0;   % 기본: 0 dBsm = 1
+    end
+    
+    %% 기본 파라미터 추출
+    lambda = RadarParams.Waveform.lambda_c;
+    fc = RadarParams.Waveform.fc;
+    kb = RadarParams.Basic.kb;
+    T0 = RadarParams.Basic.T0;
+    
+    % 안테나 및 경로 파라미터
+    TxPattern = RadarParams.Antenna.TxPattern;
+    RxPattern = RadarParams.Antenna.RxPattern;
+    NumTx = RadarParams.Antenna.NumTx;
+    NumRx = RadarParams.Antenna.NumRx;
+    
+    % 수신 경로 파라미터
+    rxPathGain_dB = RadarParams.Rxpath.rxPathGain_dB;
+    system_NF_dB = RadarParams.Rxpath.system_NF_dB;
+    
+    % RCS (선형값)
+    rcs_target = 10^(target_rcs_dBsm / 10);
+    
+    %% 평균 2D 안테나 패턴 생성 (1D -> 2D 변환 포함)
+    % 공통 그리드 설정 (높은 해상도)
+    az_common = -90:1:90;
+    el_common = -90:1:90;
+    [AZ_common_grid, EL_common_grid] = meshgrid(az_common, el_common);
+    
+    % TX 패턴들을 2D로 변환 및 평균
+    avg_tx_gain_2d = zeros(length(el_common), length(az_common));
+    for tx = 1:NumTx
+        if isfield(TxPattern(tx), 'gain_az_dBi')  % 1D 패턴
+            az_angles = TxPattern(tx).az_angles;
+            el_angles = TxPattern(tx).el_angles;
+            gain_az = TxPattern(tx).gain_az_dBi;
+            gain_el = TxPattern(tx).gain_el_dBi;
+            
+            % 각 패턴의 최대값 저장
+            max_gain_az = max(gain_az);
+            max_gain_el = max(gain_el);
+            max_gain_ref = max(max_gain_az, max_gain_el);
+            
+            % Normalize (최대값 = 0 dB)
+            gain_az_norm = gain_az - max_gain_az;
+            gain_el_norm = gain_el - max_gain_el;
+            
+            % 정규화된 패턴 보간
+            gain_az_interp = interp1(az_angles, gain_az_norm, AZ_common_grid, 'linear', 'extrap');
+            gain_el_interp = interp1(el_angles, gain_el_norm, EL_common_grid, 'linear', 'extrap');
+            
+            % 2D로 결합하고 최대 이득 더하기
+            tx_gain_2d = gain_az_interp + gain_el_interp + max_gain_ref;
+        else  % 2D 패턴
+            az_angles = TxPattern(tx).az_angles;
+            el_angles = TxPattern(tx).el_angles;
+            gain_dBi = TxPattern(tx).gain_dBi;
+            [AZ_grid, EL_grid] = ndgrid(az_angles, el_angles);
+            F = scatteredInterpolant(AZ_grid(:), EL_grid(:), gain_dBi(:), 'linear', 'nearest');
+            tx_gain_2d = F(AZ_common_grid, EL_common_grid);
+        end
+        avg_tx_gain_2d = avg_tx_gain_2d + tx_gain_2d;
+    end
+    avg_tx_gain_2d = avg_tx_gain_2d / NumTx;
+    
+    % RX 패턴들을 2D로 변환 및 평균 (동일한 방식)
+    avg_rx_gain_2d = zeros(length(el_common), length(az_common));
+    for rx = 1:NumRx
+        if isfield(RxPattern(rx), 'gain_az_dBi')  % 1D 패턴
+            az_angles = RxPattern(rx).az_angles;
+            el_angles = RxPattern(rx).el_angles;
+            gain_az = RxPattern(rx).gain_az_dBi;
+            gain_el = RxPattern(rx).gain_el_dBi;
+            
+            % 각 패턴의 최대값 저장
+            max_gain_az = max(gain_az);
+            max_gain_el = max(gain_el);
+            max_gain_ref = max(max_gain_az, max_gain_el);
+            
+            % Normalize (최대값 = 0 dB)
+            gain_az_norm = gain_az - max_gain_az;
+            gain_el_norm = gain_el - max_gain_el;
+            
+            % 정규화된 패턴 보간
+            gain_az_interp = interp1(az_angles, gain_az_norm, AZ_common_grid, 'linear', 'extrap');
+            gain_el_interp = interp1(el_angles, gain_el_norm, EL_common_grid, 'linear', 'extrap');
+            
+            % 2D로 결합하고 최대 이득 더하기
+            rx_gain_2d = gain_az_interp + gain_el_interp + max_gain_ref;
+        else  % 2D 패턴
+            az_angles = RxPattern(rx).az_angles;
+            el_angles = RxPattern(rx).el_angles;
+            gain_dBi = RxPattern(rx).gain_dBi;
+            [AZ_grid, EL_grid] = ndgrid(az_angles, el_angles);
+            F = scatteredInterpolant(AZ_grid(:), EL_grid(:), gain_dBi(:), 'linear', 'nearest');
+            rx_gain_2d = F(AZ_common_grid, EL_common_grid);
+        end
+        avg_rx_gain_2d = avg_rx_gain_2d + rx_gain_2d;
+    end
+    avg_rx_gain_2d = avg_rx_gain_2d / NumRx;
+    
+    %% TX 전력 및 공통 파라미터 계산
+    % TX 전력
+    pa_profile_freq = RadarParams.RFOutput.PA_Profile.freqs;
+    pa_profile_power_dbm = RadarParams.RFOutput.PA_Profile.power_dBm;
+    ptx_dbm = interp1(pa_profile_freq, pa_profile_power_dbm, fc, 'linear', 'extrap');
+    ptx_w = 10^((ptx_dbm - 30) / 10);
+    
+    % 경로 손실 및 잡음 계산 (모든 각도에서 공통)
+    path_loss_factor = (4 * pi * target_range_m)^2;
+    rxGain_linear = 10^(rxPathGain_dB / 10);
+    noise_power_w = kb * T0 * RadarParams.Waveform.fs_adc;
+    system_NF_linear = 10^(system_NF_dB / 10);
+    total_noise_power_w = noise_power_w * system_NF_linear * rxGain_linear;  % RX 이득 포함
+    
+    %% 각도별 SNR 계산 (2D 안테나 패턴 직접 사용 - 벡터화 연산)
+    % X축: Azimuth, Y축: Elevation, Z축: SNR
+    azimuth_deg = -90:1:90;   % X축: -90 ~ 90도, 1도 단위
+    elevation_deg = -90:1:90;  % Y축: -90 ~ 90도, 1도 단위
+    
+    % az_common과 elevation_deg가 동일한 그리드이므로 인덱스 매칭
+    % 안테나 이득 추출 (dB)
+    g_tx_db_grid = avg_tx_gain_2d;  % [num_el x num_az]
+    g_rx_db_grid = avg_rx_gain_2d;  % [num_el x num_az]
+    
+    % 이득을 선형으로 변환
+    g_tx_linear_grid = 10.^(g_tx_db_grid / 10);
+    g_rx_linear_grid = 10.^(g_rx_db_grid / 10);
+    
+    % SNR 계산: 벡터화 연산 (스칼라 항 × 2D 배열)
+    p_rx_w = (ptx_w * g_tx_linear_grid .* g_rx_linear_grid * (lambda^2) * rcs_target) / ((path_loss_factor^2) * (4 * pi));
+    p_rx_after_rxgain_w = p_rx_w * rxGain_linear;
+    snr_linear = p_rx_after_rxgain_w / total_noise_power_w;
+    snr_coverage_2d = 10 * log10(max(snr_linear, eps));
+    
+    %% 1D CUT 추출 (elevation=0에서의 Azimuth cut, azimuth=0에서의 Elevation cut)
+    [~, el_idx_zero] = min(abs(elevation_deg - 0));
+    snr_az_cut = snr_coverage_2d(el_idx_zero, :);  % elevation=0
+    
+    [~, az_idx_zero] = min(abs(azimuth_deg - 0));
+    snr_el_cut = snr_coverage_2d(:, az_idx_zero);  % azimuth=0
+    
+    %% Cartesian 좌표계 변환 (Range, Azimuth, Elevation -> x, y, z)
+    [AZ_deg_grid, EL_deg_grid] = meshgrid(azimuth_deg, elevation_deg);
+    x_grid_m = target_range_m .* cosd(EL_deg_grid) .* cosd(AZ_deg_grid);
+    y_grid_m = target_range_m .* cosd(EL_deg_grid) .* sind(AZ_deg_grid);
+    z_grid_m = target_range_m .* sind(EL_deg_grid);
+
+    %% Coverage 정보 통계
+    snr_2d_vec = snr_coverage_2d(:);
+    
+    coverage_info.azimuth_deg = azimuth_deg;
+    coverage_info.elevation_deg = elevation_deg;
+    coverage_info.snr_coverage_2d = snr_coverage_2d;
+    coverage_info.snr_az_cut = snr_az_cut;
+    coverage_info.snr_el_cut = snr_el_cut;
+    coverage_info.target_range_m = target_range_m;
+    coverage_info.target_rcs_dBsm = target_rcs_dBsm;
+    coverage_info.x_grid_m = x_grid_m;
+    coverage_info.y_grid_m = y_grid_m;
+    coverage_info.z_grid_m = z_grid_m;
+    coverage_info.mean_snr = mean(snr_2d_vec);
+    coverage_info.max_snr = max(snr_2d_vec);
+    coverage_info.min_snr = min(snr_2d_vec);
+    [~, max_idx_2d] = max(snr_2d_vec);
+    [max_el_idx_2d, max_az_idx_2d] = ind2sub(size(snr_coverage_2d), max_idx_2d);
+    coverage_info.max_snr_azimuth = azimuth_deg(max_az_idx_2d);
+    coverage_info.max_snr_elevation = elevation_deg(max_el_idx_2d);
+    coverage_info.max_snr_x_m = x_grid_m(max_el_idx_2d, max_az_idx_2d);
+    coverage_info.max_snr_y_m = y_grid_m(max_el_idx_2d, max_az_idx_2d);
+    coverage_info.max_snr_z_m = z_grid_m(max_el_idx_2d, max_az_idx_2d);
+    
+    %% 3D + 1D Cut 시각화
+    fig = figure('Name', 'Coverage Analysis - 3D + 1D Cut');
+    set(fig, 'Position', [100, 100, 1600, 900]);
+
+    % Subplot 1: x-SNR Cut (elevation=0)
+    subplot(2, 3, 1);
+    x_cut_m = target_range_m .* cosd(azimuth_deg);
+    plot(x_cut_m, snr_az_cut, 'b-', 'LineWidth', 2);
+    hold on;
+    [~, max_idx_az] = max(snr_az_cut);
+    plot(x_cut_m(max_idx_az), snr_az_cut(max_idx_az), 'r*', 'MarkerSize', 15, 'LineWidth', 2);
+    grid on;
+    xlabel('x (m)');
+    ylabel('SNR (dB)');
+    title('1D CUT: elevation = 0 deg');
+    hold off;
+    
+    % Subplot 2: z-SNR Cut (azimuth=0)
+    subplot(2, 3, 2);
+    z_cut_m = target_range_m .* sind(elevation_deg);
+    plot(z_cut_m, snr_el_cut, 'g-', 'LineWidth', 2);
+    hold on;
+    [~, max_idx_el] = max(snr_el_cut);
+    plot(z_cut_m(max_idx_el), snr_el_cut(max_idx_el), 'r*', 'MarkerSize', 15, 'LineWidth', 2);
+    grid on;
+    xlabel('z (m)');
+    ylabel('SNR (dB)');
+    title('1D CUT: azimuth = 0 deg');
+    hold off;
+    
+    % Subplot 3: x-y top view (color = SNR at elevation=0)
+    subplot(2, 3, 3);
+    x_top_m = target_range_m .* cosd(azimuth_deg);
+    y_top_m = target_range_m .* sind(azimuth_deg);
+    scatter(x_top_m, y_top_m, 45, snr_az_cut, 'filled');
+    axis equal;
+    grid on;
+    cb = colorbar;
+    ylabel(cb, 'SNR (dB)');
+    xlabel('x (m)');
+    ylabel('y (m)');
+    title('Top View (elevation = 0 deg)');
+    
+    % Subplot 4-5: 3D Surface (geometry = x,y,z, color = SNR)
+    subplot(2, 3, 4:5, 'replace');
+    surf(x_grid_m, y_grid_m, z_grid_m, snr_coverage_2d, 'EdgeColor', 'none');
+    colormap(jet);
+    cb_3d = colorbar;
+    ylabel(cb_3d, 'SNR (dB)');
+    xlabel('x (m)');
+    ylabel('y (m)');
+    zlabel('z (m)');
+    title('3D Coverage in Cartesian Coordinates (Click to inspect)');
+    view(45, 30);
+    grid on;
+    hold on;
+    plot3(coverage_info.max_snr_x_m, coverage_info.max_snr_y_m, coverage_info.max_snr_z_m, 'r*', 'MarkerSize', 20, 'LineWidth', 2);
+    hold off;
+    
+    % Datacursor mode 활성화 (클릭 기능)
+    dcm_obj = datacursormode(fig);
+    dcm_obj.Enable = 'on';
+    set(dcm_obj, 'UpdateFcn', @datatip_update_callback);
+    set(dcm_obj, 'SnapToDataVertex', 'on');
+    
+    % Help text
+    fprintf('\n>>> Data Cursor Mode ENABLED <<<\n');
+    fprintf('Instructions:\n');
+    fprintf('  1. Left-click on the 3D surface to inspect points\n');
+    fprintf('  2. Tooltip shows x, y, z (m) and SNR[dB]\n');
+    fprintf('  3. Press Escape or click "Disable Data Cursor" in Figure Tools to deactivate\n\n');
+    
+    %% Nested function for datacursor callback
+    function output_txt = datatip_update_callback(~, event)
+        pos = event.Position;
+        x_val = pos(1);
+        y_val = pos(2);
+        z_val = pos(3);
+
+        dist2 = (x_grid_m - x_val).^2 + (y_grid_m - y_val).^2 + (z_grid_m - z_val).^2;
+        [~, nearest_idx] = min(dist2(:));
+        [nearest_el_idx, nearest_az_idx] = ind2sub(size(dist2), nearest_idx);
+        snr_val = snr_coverage_2d(nearest_el_idx, nearest_az_idx);
+
+        output_txt = {
+            ['x: ' num2str(x_val, '%.3f') ' m']
+            ['y: ' num2str(y_val, '%.3f') ' m']
+            ['z: ' num2str(z_val, '%.3f') ' m']
+            ['SNR[dB]: ' num2str(snr_val, '%.3f')]
+        };
+    end
+
+    % Subplot 6: x-z side view (azimuth=0, color=SNR)
+    subplot(2, 3, 6);
+    x_side_m = target_range_m .* cosd(elevation_deg);
+    z_side_m = target_range_m .* sind(elevation_deg);
+    scatter(x_side_m, z_side_m, 45, snr_el_cut, 'filled');
+    grid on;
+    cb_side = colorbar;
+    ylabel(cb_side, 'SNR (dB)');
+    xlabel('x (m)');
+    ylabel('z (m)');
+    title('Side View (azimuth = 0 deg)');
+
+    % 전체 타이틀
+    sgtitle(sprintf('3D Coverage (x,y,z) | Max SNR: %.2f dB at (%.2f, %.2f, %.2f) m', ...
+                    coverage_info.max_snr, coverage_info.max_snr_x_m, coverage_info.max_snr_y_m, coverage_info.max_snr_z_m), 'FontSize', 12);
+    
+    %% 통계 출력
+    fprintf('\n===== 3D COVERAGE ANALYSIS REPORT (Cartesian x,y,z) =====\n');
+    fprintf('Target Configuration:\n');
+    fprintf('  - Range: %.1f m\n', target_range_m);
+    fprintf('  - RCS: %.1f dBsm\n', target_rcs_dBsm);
+    fprintf('  - Analysis Angles: Azimuth ±90 deg, Elevation ±90 deg\n');
+    fprintf('\nSNR Statistics (Full Grid):\n');
+    fprintf('  - Mean SNR: %.2f dB\n', coverage_info.mean_snr);
+    fprintf('  - Max SNR: %.2f dB @ (x,y,z)=(%.2f, %.2f, %.2f) m\n', coverage_info.max_snr, coverage_info.max_snr_x_m, coverage_info.max_snr_y_m, coverage_info.max_snr_z_m);
+    fprintf('  - Min SNR: %.2f dB\n', coverage_info.min_snr);
+    fprintf('  - SNR Range: %.2f dB\n', coverage_info.max_snr - coverage_info.min_snr);
+    fprintf('\n1D CUT Statistics:\n');
+    fprintf('  - elevation=0 cut: Max=%.2f dB, Min=%.2f dB\n', max(snr_az_cut), min(snr_az_cut));
+    fprintf('  - azimuth=0 cut: Max=%.2f dB, Min=%.2f dB\n', max(snr_el_cut), min(snr_el_cut));
+    fprintf('System Parameters:\n');
+    fprintf('  - TX Power: %.2f dBm\n', ptx_dbm);
+    fprintf('  - RX Gain: %.1f dB\n', rxPathGain_dB);
+    fprintf('  - System NF: %.1f dB\n', system_NF_dB);
+    fprintf('=============================================\n\n');
+end

Main.m

@@ -10,6 +10,17 @@ currentFilePath = mfilename('fullpath');
 currentFolder = fileparts(currentFilePath);
 addpath(genpath(currentFolder));
 
+%% =================== 시각화 토글 ===================
+% 각 figure를 개별적으로 on/off 할 수 있습니다.
+PlotToggle.range_profile   = false;   % Step 8 Range Profile
+PlotToggle.tx_single       = false;   % Figure 1 Single chirp waveform
+PlotToggle.tx_multi        = false;   % Figure 2 Multi chirp waveform
+PlotToggle.tx_antenna      = false;   % Figure 3 TX antenna pattern
+PlotToggle.rx_antenna      = false;   % Figure 4 RX antenna pattern
+PlotToggle.rd_map          = false;   % Figure 5 Range-Doppler map
+PlotToggle.cfar            = false;   % Figure 6 CFAR detections
+PlotToggle.coverage        = true;   % Figure 7 Coverage analysis
+
 %% =================== 파라미터 입력 ===================
 
 % 1) 기본 물리 파라미터
@@ -205,6 +216,7 @@ adc_digital_expanded = reshape(adc_digital, [size(adc_digital,1), 1, size(adc_di
 [range_data, r_axis] = process_range_fft_lpf(adc_digital_expanded, RadarParams);
 
 % step 8. Range Profile 시각화 (1번 채널, 1번 처프)
+if PlotToggle.range_profile
     figure('Name', 'Range Profile with Ideal LPF');
     plot(r_axis, 20*log10(abs(squeeze(range_data(1,1,1,:)))));
     grid on; hold on;
@@ -214,6 +226,7 @@ title(['Range Profile (LPF Cut-off: ', num2str(RadarParams.Rxpath.fc_lpf/1e6), '
 
     % LPF 컷오프 지점 표시
     xline((RadarParams.Rxpath.fc_lpf * RadarParams.Basic.c)/(2*RadarParams.Waveform.Slope), '--r', 'LPF Cut-off');
+end
 
 % step 9. Doppler-FFT 수행
 [rd_cube, v_axis] = process_doppler_fft(range_data, RadarParams);
@@ -232,21 +245,39 @@ idx_single = (t <= T_chirp);
 t_single = t(idx_single);
 tx_mask_single = tx_mask(idx_single);
 
+fig_single = [];
+if PlotToggle.tx_single
     fig_single = visualize_tx_waveform(t_single, RadarParams.Waveform.Timing, RadarParams.Waveform.fc, RadarParams.Waveform.f_start, RadarParams.Waveform.Slope, tx_mask_single, RadarParams.Waveform.nonideal.peak_phase_error, RadarParams.Waveform.nonideal.f_ripple);
+end
 
 % [Figure 2] 다중 처프 프레임 시퀀스 및 MIMO 변조 확인
 % (수정됨: mimoMode와 NumTx 변수를 추가로 전달)
+fig_multi = [];
+if PlotToggle.tx_multi
     fig_multi = visualize_multi_tx_waveform(t, RadarParams.Waveform.Timing, RadarParams.Waveform.fc, RadarParams.Waveform.f_start, RadarParams.Waveform.Slope, tx_mask, NumChirps, RadarParams.Waveform.mimoMode, NumTx);
+end
 
 % --- [ Figure 3, 4: 안테나 방사 패턴 단면 도시 ] ---
 % 'TX'와 'RX'라는 이름을 넘겨주어 그래프 타이틀과 범례를 구분합니다.
+fig_tx_ant = [];
+if PlotToggle.tx_antenna
     fig_tx_ant = visualize_antenna_pattern(TxPattern, 'TX');
+end
+
+fig_rx_ant = [];
+if PlotToggle.rx_antenna
     fig_rx_ant = visualize_antenna_pattern(RxPattern, 'RX');
+end
 
 % [Figure 5] Range-Doppler Map 시각화 (NumRx NCI RDM)
+fig_rd_map = [];
+if PlotToggle.rd_map
     fig_rd_map = visualize_rd_map_with_spurs(target_rd_map, r_axis, v_axis, Target, RadarParams.SpurParams, RadarParams, RadarParams.Waveform.Slope);
+end
 
 % [Figure 6] CFAR 탐지 결과 시각화 (2D MAP 위 원 마커)
+fig_cfar = [];
+if PlotToggle.cfar
     fig_cfar = figure('Name', 'CFAR Detections on NCI RDM');
     imagesc(r_axis, v_axis, 20*log10(abs(target_rd_map)));
     axis xy;
@@ -266,6 +297,19 @@ if ~isempty(cfar_detections)
     end
 
     hold off;
+end
+
+% ================= Coverage Analysis (Performance Analysis) =================
+% [Figure 7] Angular Coverage 분석: 2D 안테나 패턴 기반 효율적 SNR 계산
+% 거리 100m, RCS 0 dBsm 표적의 각도별 SNR 분석
+snr_coverage_2d = [];
+azimuth_deg = [];
+elevation_deg = [];
+coverage_info = [];
+fig_coverage = [];
+if PlotToggle.coverage
+    [snr_coverage_2d, azimuth_deg, elevation_deg, coverage_info, fig_coverage] = analyze_coverage(RadarParams, 10, 0);
+end