A python module for computing the Ambiguity Function for analyzing radar signals, as outlined in 'Radar Signals' by Levanon & Mozeson.
- distribute>=0.7.3
- numpy>=1.9.1
- scipy>=0.15.1
- If using a virtualenv, any suitable display backend for matplotlib
- matplotlib>=1.4.2
Please ensure the above dependencies are met before running this script
Numpy, Scipy and matplotlib can be installed by:
pip install numpy scipy matplotlib
Or, by using the bundled requirements.txt:
pip install --upgrade --force-reinstall -r requirements.txt
This is the function signature for the 'ambiguity' method:
def ambiguity(u_basic=DEFAULT_SIGNAL,
fcode=True,
f_basic=None,
F=0,
K=0,
T=0,
N=0,
sr=0,
plot_title="",
plot1_file=None,
plot2_file=None,
plot_format="svg",
plot_mesh=True,
elev=50,
azim=-135):
""" Compute Ambiguity & generate Plots for given input parameters
Params:
-------
u_basic: numpy.ndarray or array-like. Input signal.
fcode: bool True if frequency coding allowed, false otherwise
f_basic: numpy.ndarray or array-like. Frequency coding in
units of 1/tb (row vector of same length)
F: int. Maximal Doppler shift for ambiguity in plot
[in units of 1/Mtb] (e.g. 1)
K: int. Number of Doppler grid points for calculation (e.g. 100)
T: float. Maximal Delay for ambiguity plot [in units of Mtb]
N: int. Number of delay grid points on each side (e.g. 100)
sr: int/float. Over sampling ratio (>=1) (e.g. 10)
plot1_file: str. Name of file where first plot will be stored.
If 'None', pops up an itneractive window to display this plot.
plot2_file: str. Name of file where second plot will be stored.
If 'None', pops up an itneractive window to display this plot.
plot_format: str. Output format for plot. (e.g. 'svg', 'png', 'pdf'
etc. Check matplotlib docs for supported formats.)
plot_mesh: bool. If True (default), plots a mesh, if False plots a
surface.
elev: float.(default=50) Elevation for 3-D plot viewpoint.
azim: float.(default=-135) Azimuth in degrees for 3-D plot viewpoint.
Returns:
--------
(delay, freq, a): 3-tuple of array_like's, where delay, freq and a
are the time, frequence and amplitude values.
"""
To use, first import the ambiguity module as follows:
from ambiguity import ambiguity
Then, set up the input parameters for calling the method, for e.g.:
import numpy as np
u_basic = np.ones((1, 51))
fcode = True
f_basic = np.dot(0.0031,
np.array(np.arange(-25, 26)))
F = 6
K = 360
T = 1.1
N = 360
sr = 10
plot_title = 'LFM' # The title to print in the plots
plot1_file = 'fig_1.png' #Optional
plot2_file = 'fig_2.png' #Optional
plot_format = 'png' #Optional
plot_mesh = True #Optional
Now call the ambiguity function with the above parameters:
ambiguity(u_basic,
fcode,
f_basic,
F,
K,
T,
N,
sr,
plot_title,
plot1_file,
plot2_file,
plot_mesh)
if plot1_file and plot2_file are None or not given, the function will attempt to pop up a matplotlib interactive display to show the plot.
You can use the elev and azim optional parameters to set up the initial view point in the 3-D plot. The plot_mesh boolean argument, (default: True), decides whether a mesh grid or a colormapped surface is plotted in the 3-D plot.
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