An iterative method for array pattern synthesis

Wu, Lixue; Zieliński, A.

doi:10.1109/joe.1993.236366

Cited by 20 publications

(10 citation statements)

References 17 publications

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“…It is evident that the optimization problems (23)-(25) include the optimal array pattern synthesis problems in refs. [13][14][15][16][17][18][19][20][21][22][23][24][25][26] as their special cases. Therefore, all the optimal array pattern synthesis problems can be solved by using the SOCP approach, which shows the flexibility of SOCP.…”

Section: Design Of Beamformersmentioning

confidence: 99%

“…The convergence of the iterations in general cannot be guaranteed. A different class of algorithms has been developed by formulating synthesis problems as quadratic programming problems [16][17][18][19][20][21] in which the sum of the squared synthesis error between the synthesized pattern and the desired pattern is minimized. This class of algorithms is more flexible than the adaptive array theory methods.…”

Section: Introductionmentioning

confidence: 99%

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Optimal design and verification of temporal and spatial filters using second-order cone programming approach

Yan

2006

SCI CHINA SER F

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Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also presented to optimize these criteria chosen. There are many drawbacks in these methods. In this paper, we introduce a unified framework for optimal design of temporal and spatial filters. Most of the optimal design problems of FIR filters and beamformers are included in the framework. It is shown that all the design problems can be reformulated as convex optimization form as the second-order cone programming (SOCP) and solved efficiently via the well-established interior point methods. The main advantage of our SOCP approach as compared with earlier approaches is that it can include most of the existing methods as its special cases, which leads to more flexible designs. Furthermore, the SOCP approach can optimize multiple required performance measures, which is the drawback of earlier approaches. The SOCP approach is also developed to optimally design temporal and spatial two-dimensional filter and spatial matrix filter. Numerical results demonstrate the effectiveness of the proposed approach.

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Section: Design Of Beamformersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal design and verification of temporal and spatial filters using second-order cone programming approach

Yan

2006

SCI CHINA SER F

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“…This suggests an alternative iteration scheme in which sidelobe 1 In [13], we show how to identify the lowest admissible sidelobe level. in mainlobe region in side lobe region (8) if otherwise (9) Fig. 4.…”

Section: B Peak-only Iterationmentioning

confidence: 99%

Pattern synthesis for arbitrary arrays using an adaptive array method

Zhou

Ingram

1999

IEEE Trans. Antennas Propagat.

154

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This paper presents a new pattern synthesis algorithm for arbitrary arrays based on adaptive array theory. With this algorithm, the designer can efficiently control both mainlobe shaping and sidelobe levels. The element weights optimize a weighted L 2 norm between desired and achieved patterns. The values of the weighting function in the L 2 norm, interpreted as imaginary jammers as in Olen and Compton's method, are iterated to minimize exceedance of the desired sidelobe levels and minimize the absolute difference between desired and achieved mainlobe patterns. The sidelobe control can be achieved by iteration only on sidelobe peaks. In comparison to Olen and Compton's method, the new algorithm provides a great improvement in mainlobe shaping control. Example simulations, including both nonuniform linear and planar arrays, are shown to illustrate the effectiveness of this algorithm.

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“…For the array with more general geometry and arbitrary element responses, the quadratic programming method [54], semidefinite programming method [55], numerical methods based on the adaptive array theory [56,57], iterative methods [58][59][60], support vector machine method [61], and so on, are developed to synthesize the narrowband beampattern.…”

Section: Iv) Broadband Pattern Synthesismentioning

confidence: 99%

Array signal processing techniques for broadband beamforming

Huang¹

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An iterative method for array pattern synthesis

Cited by 20 publications

References 17 publications

Optimal design and verification of temporal and spatial filters using second-order cone programming approach

Optimal design and verification of temporal and spatial filters using second-order cone programming approach

Pattern synthesis for arbitrary arrays using an adaptive array method

Array signal processing techniques for broadband beamforming

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