Description
Calculated beam pattern in Fourier space of a unitary input given two sparsely sampled synthetic aperture arrays: 1. a regularly spaced array sampled at 2*lambda, where lambda is the wavelength of the 40 GHz signal, and 2. the regularly spaced array with random perturbations (of order ~<lambda) to the (x,y) spatial location of each sample point. This dataset is published in "An Overview of Advances in Signal Processing Techniques for Classical and Quantum Wideband Synthetic Apertures" by Vouras, et al. in IEEE Selected Topics in Signal Processing Recent Advances in Wideband Signal Processing for Classical and Quantum Synthetic Apertures.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| Matlab code to recreate Fig. 20 | Unknown | Matlab script will generate the exact data provided in "Fig20_GratingLobesDueToSparseSamplingGrid.csv" and will plot the output. This script requires "compute_FFT.m" to be located in the same workspace or directory. To generate the output data given in "Fig22_OptimizedSparseArrayBeamPattern.csv", one can replace "sparse_array_x" (line 20) and "sparse_array_y" (line 21) with the first two columns of "Fig21_SparseArrayBeforeAndAfterOptimization.csv" ("Xposition_m" and "Yposition_m_After"). | Open resource |
| Matlab function to compute 2D FFT | Unknown | Matlab function to compute the two-dimensional spatial Fast Fourier Transform (FFT) of an input spatially sampled array along x and y (input variables "array_x" and "array_y") given a wavelength ("lambda"), Fourier space sampling "U" and "V", and signal magnitude at each spatial location ("temp"). | Open resource |
| Data to generate Fig. 20: Grating Lobes Due to Sparse Sampling Grid | Unknown | Sparsely sampled lattices on a regular grid introduce grating lobes in the beampattern as demonstrated by this simulated dataset of the beam pattern observed in Fourier space (u=sin(theta)cos(phi), v=sin(theta)sin(phi), where theta is the elevation angle and phi is the azimuth angle) when a regularly sampled sparse array is used to acquire the signal. | Open resource |
| Data to generate Fig. 21: Sparse Array Before and After Optimization | Unknown | A simple approach for mitigating grating lobes in a sparse lattice is to perturb the regularity of the grid spacing by applying a random offset to each spatial sample. These data compare the spatial locations of a regularly sampled sparse array labeled as "Before" to the randomly perturbed sparse array sample locations labeled as "After". | Open resource |
| Data to generate Fig. 22: Optimized Sparse Array Beam Pattern | Unknown | Periodicity in the beam pattern, here calculated and reported in Fourier space (u=sin(theta)cos(phi), v=sin(theta)sin(phi), where theta is the elevation angle and phi is the azimuth angle), is eliminated by the use of the randomly perturbed spatial sample locations of the sparse array. These simulated data show the outcome of using the sparse array labeled "After" in dataset "Fig21_SparseArrayBeforeAndAfterOptimization.csv" and provides a comparison to this randomized perturbation to the regular sampling output given in "Fig20_GratingLobesDueToSparseSamplingGrid.csv". | Open resource |
| Dataset use, references, and contact information | Unknown | "Readme" file provided additional information relating to "Grating Lobes and Spatial Aliasing in Sparse Array Beampatterns" simulation dataset. | Open resource |