import pickle from Unpack import unpack from read_files import read_radar_data, read_motion_data from data_align import align_data motion_data = read_motion_data("../Raw_Data/UASSAR4_rail_diagonal.csv","UASSAR4") radar_data = read_radar_data("../Raw_Data/railTestDiagonal.pkl") aligned_data = align_data(radar_data,motion_data,272,1844,5368) Pulses = aligned_data[0] Final_Motion = aligned_data[1] print(Final_Motion) aligned_data[2] = radar_data[2] with open('parrot.pkl', 'wb') as f: pickle.dump(aligned_data,f) f.close()
from data_align import align_data from GeneralAlignedRangeTimeGraph import AlignedGraph from FastLinInt import FastBackProjection from LinInt import BackProjection from Deconvolution import deconvolute from plotRTI import plotRTI from helper_functions import linear_interp_nan import pickle #Converts motion and RADAR data to the right data structures unpack("../Raw_Data/uavsar1flight7") #Loads data from the RADAR motion_data = read_motion_data("../Raw_Data/UAVSAR1Flight7.csv", "UAVSAR1") motion_data = linear_interp_nan(motion_data[1], motion_data[0]) radar_data = read_radar_data("data.pkl", 580, 0.3) #580, 0.30 is probably good #Performs RCS correction radar_data = rcs(radar_data) #Plot RTI for radar_data plotRTI(radar_data) #Set parameters #Take motion_start and motion_end from .tak file video #Estimate radar_start from the plotRTI above, initially comment out code below radar_start = 300 #Initial 500 380 for flight 6 300 for flight 7 motion_start = 3850 #5200 flight 6 3900 flight 7 2411 flight 8 motion_end = 34129 #16400 flight 6 34129 flight 7 29126 flight 8 #Aligns data
from data_align import align_data from GeneralAlignedRangeTimeGraph import AlignedGraph from LinInt import BackProjection from Deconvolution import deconvolute from plotRTI import plotRTI from FastLinInt import FastBackProjection from helper_functions import linear_interp_nan import matplotlib.pyplot as plt #Converts motion and RADAR data to the right data structures unpack("../Raw_Data/uavsar1flight4") #Loads data from the RADAR motion_data = read_motion_data("../Raw_Data/UAVSAR1Flight4.csv", "UAVSAR1") motion_data = linear_interp_nan(motion_data[1], motion_data[0]) radar_data = read_radar_data("data.pkl", 580, 0.25) #580, 0.25 is probably good #Performs RCS correction radar_data = rcs(radar_data) #Plot RTI for radar_data plotRTI(radar_data) #Set parameters #Take motion_start and motion_end from .tak file video #Estimate radar_start from the plotRTI above, initially comment out code below radar_start = 510 #Flight4: 505, FLight3: 135, Flight2: 113 motion_start = 3450 #Flight2: 3300, Flight3: 2400, FLight4: 3450, Flight5: 4477 motion_end = 14462 #Flight2: 24000, Flight3: 15382, Flight4: 14462, Flight5: 14201 #Aligns data
from data_align import align_data from AlignedRangeTimeGraph import AlignedGraph from LinInt import BackProjection from read_intensity import read_intensity from Deconvolution import deconvolute from backprojection import interp_approach, main #Ramu's backprojection from rcs import rcs #from FastLinInt import FastBackProjection import numpy as np import matplotlib.pyplot as plt #Converts motion and RADAR data to the right data structures #unpack("../Raw_Data/uavsar1flight1") #Currently commented out because unused #Loads data from the RADAR motion_data = read_motion_data("../Raw_Data/UAVSAR1Flight1.csv", "UAVSAR1") radar_data = read_radar_data("UAVSAR1Flight1.pkl", 580, 0.30) radar_data = rcs(radar_data) #Finds the first point of the motion data that it starts to move #motion_start = find_i_of_first_motion(motion_data) #Finds the last point of the motion data that it moves #motion_end = find_i_of_last_motion(motion_data) #Finds the first point in the radar data that it starts to move #radar_start = find_point_one_radar(radar_data) radar_start = 600 motion_start = 6600 motion_end = 29545 #Aligns data, currently using frames given in function definition
from pulson440_unpack import unpack from read_files import read_radar_data, read_motion_data from radar_movement import find_point_one_radar, find_i_of_first_motion, find_i_of_last_motion from data_align import align_data from GeneralAlignedRangeTimeGraph import AlignedGraph from FastLinInt import BackProjection from read_intensity import read_intensity from Deconvolution import deconvolute from backprojection import interp_approach, main #Ramu's backprojection #Converts motion and RADAR data to the right data structures unpack("../Raw_Data/uavsar1flight1") #Currently commented out because unused #Loads data from the RADAR motion_data = read_motion_data("../Raw_Data/UAVSAR1Flight1.csv","UAVSAR1") radar_data = read_radar_data("../Raw_Data/data.pkl") #Finds the first point of the motion data that it starts to move #motion_start = find_i_of_first_motion(motion_data) #Finds the last point of the motion data that it moves #motion_end = find_i_of_last_motion(motion_data) #Finds the first point in the radar data that it starts to move #radar_start = find_point_one_radar(radar_data) radar_start = 600 motion_start = 6600 motion_end = 29545 #Aligns data, currently using frames given in function definition
@author: Mason ''' #Import required modules from pulson440_unpack import unpack from read_files import read_radar_data, read_motion_data from radar_movement import find_point_one_radar, find_i_of_first_motion, find_i_of_last_motion from data_align import align_data from AlignedRangeTimeGraph import AlignedGraph from RangeTimeGraph import rti_graph from rcs import rcs import numpy as np import matplotlib.pyplot as plt #unpack("../Raw_data/uavsar1flight1") #Currently commented out because unused motion_data = read_motion_data("UAVSAR1Flight1.csv","UAVSAR1") radar_data = read_radar_data() #motion_start = find_i_of_first_motion(motion_data) #motion_end = find_i_of_last_motion(motion_data) #radar_start = find_point_one_radar(radar_data) motion_start = 6600 motion_end = 29545 radar_start = 600 #plt.imshow(abs(radar_data[0])) #Aligns data, currently using frames given in function definition aligned_data = align_data(radar_data,motion_data,radar_start,motion_start, motion_end) radar_end = aligned_data[2] rti_graph(radar_data,motion_data,radar_start,motion_start,motion_end,radar_end) rcs = rcs(radar_data)
from read_files import read_radar_data, read_motion_data from radar_movement import find_point_one_radar, find_i_of_first_motion, find_i_of_last_motion from data_align import align_data from AlignedRangeTimeGraph import AlignedGraph from LinInt import BackProjection from read_intensity import read_intensity from Deconvolution import deconvolute from backprojection import interp_approach, main #Ramu's backprojection from rcs import rcs import numpy as np import matplotlib.pyplot as plt #Converts motion and RADAR data to the right data structures #unpack("../Raw_data/RailSAR-record1") #Currently commented out because unused motion_data = read_motion_data("../Raw_Data/UAVSAR4Flight1.csv", "UASSAR4") radar_data = read_radar_data("../Raw_Data/UAVSAR4Flight1.pkl") #Does RCS correction new_radar_data = rcs(radar_data) #Plots RTI graph plt.figure(0) plt.set_cmap('jet') rti_ax = plt.imshow(20 * np.log10(np.abs(new_radar_data[0]))) rti_ax.axes.set_aspect('auto') plt.title('Range-Time Intensity') plt.xlabel('Range Bins') plt.ylabel('Pulse Index') cbar = plt.colorbar() cbar.ax.set_ylabel('dB') plt.show()