NawfalMotii79
47 lines
1.9 KiB
Plaintext
47 lines
1.9 KiB
Plaintext
import numpy as np
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# Constants
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MATRIX_SIZE = 83 # 83x83 matrix
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BUFFER_SIZE = MATRIX_SIZE * MATRIX_SIZE # 6889 elements
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AZIMUTH_RANGE = (-41.8, 41.8) # Azimuth range
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ELEVATION_RANGE = (41.8, -41.8) # Elevation range
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def generate_angle_grid():
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"""Generate azimuth and elevation matrices."""
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azimuth_values = np.linspace(AZIMUTH_RANGE[0], AZIMUTH_RANGE[1], MATRIX_SIZE)
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elevation_values = np.linspace(ELEVATION_RANGE[0], ELEVATION_RANGE[1], MATRIX_SIZE)
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azimuth_matrix, elevation_matrix = np.meshgrid(azimuth_values, elevation_values)
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return azimuth_matrix, elevation_matrix
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def process_radar_data(buffer):
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"""Convert buffer into an 83x83 matrix, find max value position, and get azimuth/elevation."""
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if len(buffer) != BUFFER_SIZE:
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raise ValueError(f"Invalid buffer size! Expected {BUFFER_SIZE}, got {len(buffer)}")
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# Reshape buffer into [83][83] matrix
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matrix = np.array(buffer).reshape((MATRIX_SIZE, MATRIX_SIZE))
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# Find position of the max value
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max_index = np.unravel_index(np.argmax(matrix), matrix.shape)
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# Generate azimuth and elevation mapping
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azimuth_matrix, elevation_matrix = generate_angle_grid()
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# Get azimuth and elevation for max value position
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max_azimuth = azimuth_matrix[max_index]
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max_elevation = elevation_matrix[max_index]
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return matrix, max_index, max_azimuth, max_elevation
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# Example: Simulated buffer with random values (Replace with actual RADAR data)
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np.random.seed(42) # For reproducibility
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buffer = np.random.rand(BUFFER_SIZE) # Simulated intensity values
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# Process the buffer
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matrix, max_pos, max_azimuth, max_elevation = process_radar_data(buffer)
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# Output results
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print(f"Max value found at matrix position: {max_pos}")
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print(f"Estimated Target Angles -> Azimuth: {max_azimuth:.2f}°, Elevation: {max_elevation:.2f}°")
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