import math
import numpy as np
import pmt
import scipy.constants as sc
from gnuradio import gr
class mts_general(gr.basic_block):
"""
docstring for block mts_general
"""
def __init__(self, pos, vel, rcs, fc, fs):
gr.basic_block.__init__(self,
name="mts_general",
in_sig=[np.complex64],
out_sig=[np.complex64]),
# self.set_auto_consume(False)
self.pos = np.array(pos)
self.vel = np.array(vel)
self.rcs = np.array(rcs)
self.fc = fc
self.lam = sc.c / self.fc
self.fs = fs
self.is_burst = False
self.curr_pulse = 0
# System parameters
self.PRF = 1e4
self.PRI = 1 / self.PRF
self.burst_start, self.burst_end = 0, 0
# self.set_history(5000)
def forecast(self, noutput_items, ninput_items_required):
# setup size of input_items[i] for work call
for i in range(len(ninput_items_required)):
ninput_items_required[i] = noutput_items
def general_work(self, input_items, output_items):
# Input and output data
in0 = input_items[0][:len(output_items[0])]
out = output_items[0]
# Absolute start and end sample numbers
start_n = self.nitems_read(0)
end_n = start_n + len(in0)
"""
Calculate all losses and shifts.
Currently only take the radial position and velocity relative to the
radar into account.
"""
# Free space propagation loss
R = math.sqrt(np.dot(np.transpose(self.pos), self.pos))
prop_loss = (4 * sc.pi * R / self.lam) ** 2
# Doppler shift (For now, using only the first velocity component)
dopp_freq = 2 * self.vel[0] / self.lam
dopp_shift = np.exp(
1j * 2 * sc.pi * dopp_freq * self.PRI * self.curr_pulse)
# Target reflection gain: The relation between the incident signal and
# the reflected signal y can be expressed as y = sqrt(G)*x, where G =
# (4*pi*rcs)/(lambda^2)
refl_gain = math.sqrt(4 * sc.pi * self.rcs[0] / (self.lam ** 2))
# Shift phase by -(4*pi*R) / ((1-(v/c))*lambda)
phase_shift = np.exp(
-(1j * 4 * sc.pi * R) / (1 - (self.vel[0] / sc.c)) *
self.lam)
# Delay sequence by fs*(R/c)
self.delay_samps = int(round(2 * self.fs * (R / sc.c)))
"""
Get all tags in the current call to the work function, and evaluate
the tags indicating a start of burst (SOB). If the sample number for
the burst start and end are the same (only happens on the first pulse
and at the end of an already tagged pulse), assign the burst_start to
the absolute offset of the tag and increment the current pulse number
(used in the doppler shift exponential above)
"""
tags = self.get_tags_in_range(0, start_n, end_n)
for tag in tags:
if pmt.symbol_to_string(tag.key) == "SOB":
# Finds the start of a new burst. Barring a missed tag,
# self.burst_start == self.burst_end only on the first burst
# or a new burst
if (self.burst_start == self.burst_end):
# Absolute sample number of the start of the burst
self.burst_start = tag.offset
# New pulse, so increment current pulse number
self.curr_pulse += 1
else:
# Absolute sample number of the end of the burst. Since
# this tag.offset is the start of a new burst,
# must subtract 1
self.burst_end = tag.offset
# Relative sample number of the end of the burst
n = self.burst_end - start_n
# Length of the pulse (in samples)
pulse_len = self.burst_end - self.burst_start
# This solution captures the entire burst, but pads it
# with a variable number of zeros afterwards, so a better
# solution is necessary
out[:pulse_len] = in0[n - (pulse_len):n] * refl_gain * \
phase_shift * dopp_shift / prop_loss
# Assign the next burst start to the end of the current
# burst (mostly necessary because of the above if statement)
self.burst_start = self.burst_end
return len(out)
# output_items[0][:] = input_items[0][:len(out)]
self.consume_each(len(input_items[0]))
return len(output_items[0])
bursts.png