FMCWteam.py

from pathlib import Path
import scipy.signal as signal
from signal_subspace import esprit
import numpy as np
from matplotlib.pyplot import figure, show

bytesperelement = 8  # complex64
Nplot = 20000


def load_bin(fn, start, end):
    """
  GNU Radio marshalls complex64 data in pairs, as read by np.fromfile()
  """
    with fn.open("rb") as f:
        f.seek(start * bytesperelement)
        rx_array = np.fromfile(f, "complex64", end - start)

    if 1:
        ax = figure().gca()
        ax.plot(range(start, start + rx_array[:Nplot].size), rx_array[:Nplot])
        ax.set_xlabel("sample #")
        ax.set_title("{}\n{}".format(fn.name, rx_array.dtype))
        show()

    print("rx .bin file: ", fn)

    return rx_array


def get_peaks(rx):
    peaks = signal.argrelmax(rx, order=10000)[0]

    peak_diffs = np.diff(peaks)

    if np.isfinite(peak_diffs):
        print("avg peak distance:", peak_diffs.mean())
        print("max peak distance:", peak_diffs.max())
        print("min peak distance:", peak_diffs.min())

        L = peak_diffs.min()
    else:
        L = None

    return peaks, L


def main(fn, start, end):
    fn = Path(fn).expanduser()
    # rx_array is loading the last 45% of the waveform from the file
    rx_array = load_bin(fn, start, end)
    # peak_array holds the indexes of each peak in the waveform
    # peak_distance is the smallest distance between each peak
    peak_array, peak_distance = get_peaks(rx_array)
    l = peak_distance - 1
    print("using window: ", l, "\n")
    # remove first peak
    peak_array = peak_array[1:]
    Npulse = len(peak_array) - 1
    print(Npulse, "pulses detected")
    wind = signal.hanning(l)
    Ntone = 2
    Nblockest = 160
    fs = 4e6  # [Hz]
    data = np.empty([Npulse, l])
    # set each row of data to window * (first l samples after each peak)
    for i in range(Npulse):
        data[i, :] = wind * rx_array[peak_array[i] : peak_array[i] + l]

    fb_est, sigma = esprit(data, Ntone, Nblockest, fs)
    print("fb_est", fb_est)
    print("sigma: ", sigma)
    drange = (3e8 * fb_est) / (2e6 / 0.1)
    print("range: ", drange, "\n")


if __name__ == "__main__":
    from argparse import ArgumentParser

    p = ArgumentParser()
    p.add_argument("fn", help="radar .bin file to load")
    p.add_argument("start", help="start sample to read", nargs="?", type=int, default=60000)
    p.add_argument("end", help="start sample to read", nargs="?", type=int, default=90000)
    p = p.parse_args()

    main(p.fn, p.start, p.end)