scholarly journals An ADS-Based Sparse Optimization Method for Sonar Imaging Sensor Arrays

2020 ◽  
Vol 10 (9) ◽  
pp. 3176
Author(s):  
Jiancheng Liu ◽  
Feng Shi ◽  
Yecheng Sun ◽  
Peng Li
Keyword(s):  
Sensor Array ◽  
Linear Array ◽  
Imaging System ◽  
Low Cost ◽  
Sensor Arrays ◽  
Optimization Method ◽  
Low Complexity ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Arrays

The Mills Cross sonar sensor array, achieved by the virtual element technology, is one way to build a low-complexity and low-cost imaging system while not decreasing the imaging quality. This type of sensor array is widely investigated and applied in sensor imaging. However, the Mills Cross array still holds some redundancy in sensor spatial sampling, and it means that this sensor array may be further thinned. For this reason, the Almost Different Sets (ADS) method is proposed to further thin the Mills Cross array. First, the original Mills Cross array is divided into several transversal linear arrays and one longitudinal linear array. Secondly, the Peak Side Lobe Level (PSLL) of each virtual linear array is estimated in advance. After the ADS parameters are matched according to the thinned ratio of the expectant array, all linear arrays are thinned in order. In the end, the element locations in the thinned linear array are used to determine which elements are kept or discarded from the original Mills array. Simulations demonstrate that the ADS method can be used to thin the Mills array and to further decrease the complexity of the imaging system while retaining beam performance.

Synthesis of thinned planar antenna arrays using teaching–learning-based optimization

2014 ◽  
Vol 7 (5) ◽  
pp. 557-563 ◽  
Author(s):  
Nihad I. Dib
Keyword(s):  
Antenna Arrays ◽  
Optimization Problems ◽  
Optimization Method ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Planar Antenna ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Level Reduction ◽  
Better Than

In this paper, the design of thinned planar antenna arrays of isotropic radiators with optimum side lobe level reduction is studied. The teaching–learning-based optimization (TLBO) method, a newly proposed global evolutionary optimization method, is used to determine an optimum set of turned-ON elements of thinned planar antenna arrays that provides a radiation pattern with optimum side lobe level reduction. The TLBO represents a new algorithm for optimization problems in antenna arrays design. It is shown that the TLBO provides results that are better than (or the same as) those obtained using other evolutionary algorithms.

scholarly journals Iterative GA Optimization Scheme for Synthesis of Radiation Pattern of Linear Array Antenna

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Sarayoot Todnatee ◽  
Chuwong Phongcharoenpanich
Keyword(s):  
Genetic Algorithm ◽  
Radiation Pattern ◽  
Linear Array ◽  
Weight Coefficient ◽  
Side Lobe ◽  
Array Element ◽  
Array Antenna ◽  
Side Lobe Level ◽  
Optimization Scheme ◽  
Iterative Optimization

This research has proposed the iterative genetic algorithm (GA) optimization scheme to synthesize the radiation pattern of an aperiodic (nonuniform) linear array antenna. The aim of the iterative optimization is to achieve a radiation pattern with a side lobe level (SLL) of ≤−20 dB. In the optimization, the proposed scheme iteratively optimizes the array range (spacing) and the number of array elements, whereby the array element with the lowest absolute complex weight coefficient is first removed and then the second lowest and so on. The removal (the element reduction) is terminated once the SLL is greater than −20 dB (>−20 dB) and the elemental increment mechanism is triggered. The results indicate that the proposed iterative GA optimization scheme is applicable to the nonuniform linear array antenna and also is capable of synthesizing the radiation pattern with SLL ≤ −20 dB.

scholarly journals FMCW sparse array imaging and restoration for microwave gauging

2012 ◽  
Vol 10 ◽  
pp. 333-339
Author(s):  
S. Kolb ◽  
R. Stolle
Keyword(s):  
Continuous Wave ◽  
Imaging System ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Essential Property ◽  
Sparse Array ◽  
The Cost ◽  
Array Imaging ◽  
Multistatic Radar ◽  
The Given

Abstract. The application of imaging radar to microwave level gauging represents a prospect of increasing the reliability of target detection. The aperture size of the used sensor determines the underlying azimuthal resolution. In consequence, when FMCW-based multistatic radar (FMCW: frequency modulated continuous wave) is used, the number of antennas dictates this essential property of an imaging system. The application of a sparse array leads to an improvement of the azimuthal resolution by keeping the number of array elements constant with the cost of increased side lobe level. Therefore, ambiguities occur within the imaging process. This problem can be modelled by a point spread function (PSF) which is common in image processing. Hence, an inverse system to the imaging system is needed to restore unique information of existing targets within the observed radar scenario. In general, the process of imaging is of ill-conditioned nature and therefore appropriate algorithms have to be applied. The present paper first develops the degradation model, namely PSF, of an imaging system based on a uniform linear array in time domain. As a result, range and azimuth dimensions are interdependent and the process of imaging has to be reformulated in one dimension. Matrix-based approaches can be adopted in this way. The second part applies two computational methods to the given inverse problem, namely quadratic and non-quadratic regularization. Notably, the second one exhibits an ability to suppress ambiguities. This can be demonstrated with the results of both, simulations and measurements, and enables sparse array imaging to localize point targets more unambiguously.

scholarly journals A PSO-CVX Algorithm of Sum and Difference Beam Patterns for Time-Modulated Antenna Array

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xikuan Dong ◽  
Hailin Li ◽  
Jing Tan ◽  
Jiawen Hu ◽  
Yachao Jiang
Keyword(s):  
Antenna Array ◽  
Particle Swarm Optimization Algorithm ◽  
Linear Array ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Main Band ◽  
Quadratic Constraint ◽  
First Order ◽  
Turn On ◽  
Beam Patterns

An integrated optimization of sum and difference beam for time-modulated linear antenna array is studied in this paper. The goal of sum and difference beam synthesis is to generate sum beam in the main band and difference beams in the first-order sideband with low side-lobe level through timing switches. The turn-on times of antenna array are achieved by solving a quadratic constraint linear programming; meanwhile, the opening times are optimized by particle swarm optimization algorithm. The results of linear array show that the sum and difference beam can be scanned within ± 40 degrees, with lower peak side-lobe level.

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