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()
