Optimally sparse and adaptive far-field sampling and pattern reconstruction

Optimally sparse and adaptive far-field sampling and pattern reconstruction: Approach for faster calibration of antenna system using compressed sensing

Subramani, Surya Natarajan (TU Delft Electrical Engineering, Mathematics and Computer Science)

Aslan, Y. (mentor)
Myers, N.J. (graduation committee)
Yarovoy, Alexander (mentor)

Delft University of Technology

Electrical Engineering

2023-08-31

Radiation pattern measurements is a critical step in characterizing antennas before they are used in any system for a specific application. To identify any defects or to acquire the true radiation characteristics of the antenna under test, densely sampled measurements are desired. However, this results in a time and cost expensive measurement process. Compressed sensing allows accurate reconstruction of radiation patterns using a reduced number of measurements. To ensure exact recovery, it is necessary to select an optimal sampling strategy as well as an effective reconstruction method.

In this thesis, the discrete Fourier transform and spherical harmonic expansion of the electric field are used to obtain a sparse representation of radiation patterns. As a variation from the basis pursuit optimization problem which is widely used in compressed sensing for antenna measurements, a sparsity enhancing weighted l1-norm minimization problem is considered. The weights are determined from prior information on antenna from electromagnetic simulations. The proposed method, after investigation with various antennas and comparison with existing benchmark results in a further reduction of number of required measurements. A near-optimal sampling technique is adopted to acquire measurement in an incoherent manner for exact recovery of the pattern. The performance of the method has been evaluated using error metrics specific to important parameters of the radiation pattern such as the gain, peak side lobe level and half power beam width. Radiation patterns with non-idealities and distortions have also been recovered with high accuracy from a small number of measurements using the proposed method.

Antenna measurements
Compressed sensing
Radiation patterns
sparse recovery
Spherical harmonics

http://resolver.tudelft.nl/uuid:287f05d2-9693-4845-b4ba-5ff0af50179a

Student theses

master thesis

© 2023 Surya Natarajan Subramani