High resolution beam-forming for wide-band LFM chirps using super nested arrays
In sensor array processing mutual coupling between sensors makes it difficult for estimation of parameters such as directions of arrival (DoA), resolution etc. Non-uniform sparse linear arrays have several advantages over conventional uniform linear arrays particularly in terms of reduced mutual cou...
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| Published in | Sadhana (Bangalore) Vol. 50; no. 2; p. 110 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New Delhi
Springer India
28.05.2025
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0973-7677 0256-2499 0973-7677 |
| DOI | 10.1007/s12046-025-02775-1 |
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| Abstract | In sensor array processing mutual coupling between sensors makes it difficult for estimation of parameters such as directions of arrival (DoA), resolution etc. Non-uniform sparse linear arrays have several advantages over conventional uniform linear arrays particularly in terms of reduced mutual coupling, better degrees of freedom, improved resolution, and enhanced target detection. However, it is crucial to validate the effectiveness of these array configurations using non-stationary signals like a chirp. This is because natural signals and signals employed in radar, sonar, and imaging systems demonstrate non-stationary characteristics. Chirp signals employed in passive and active systems of sonars and radars provide good noise immunity at the receiver and better range resolution. This paper explores beam-forming in the context of DoA estimation for linear frequency modulated (LFM) chirp signals using super nested arrays, by taking into account the effect of mutual coupling. Also, the performance of super nested arrays on signal detection, resolution and accuracy is compared using other popular sparse array configurations viz. co-prime and nested arrays. It is seen from the computer simulations that super nested arrays excels other non-uniform sparse arrays in terms of resolution and accuracy, intercepting LFM chirp signals. Also the development of steering vector based on fractional Fourier transform, corresponding to the center frequency of the chirp had demonstrated performance supremacy of DoA estimation algorithms over conventional Fourier transform method. |
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| AbstractList | In sensor array processing mutual coupling between sensors makes it difficult for estimation of parameters such as directions of arrival (DoA), resolution etc. Non-uniform sparse linear arrays have several advantages over conventional uniform linear arrays particularly in terms of reduced mutual coupling, better degrees of freedom, improved resolution, and enhanced target detection. However, it is crucial to validate the effectiveness of these array configurations using non-stationary signals like a chirp. This is because natural signals and signals employed in radar, sonar, and imaging systems demonstrate non-stationary characteristics. Chirp signals employed in passive and active systems of sonars and radars provide good noise immunity at the receiver and better range resolution. This paper explores beam-forming in the context of DoA estimation for linear frequency modulated (LFM) chirp signals using super nested arrays, by taking into account the effect of mutual coupling. Also, the performance of super nested arrays on signal detection, resolution and accuracy is compared using other popular sparse array configurations viz. co-prime and nested arrays. It is seen from the computer simulations that super nested arrays excels other non-uniform sparse arrays in terms of resolution and accuracy, intercepting LFM chirp signals. Also the development of steering vector based on fractional Fourier transform, corresponding to the center frequency of the chirp had demonstrated performance supremacy of DoA estimation algorithms over conventional Fourier transform method. |
| ArticleNumber | 110 |
| Author | Sreekumar, Shyama Vani Lakshmi, V Reji, Rebecca Elizabeth Kunampilavu, Sanjana Shaju Sreekumar, G Thomas, Sneha Palakunnal |
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| SubjectTerms | Algorithms Arrays Beamforming Chirp signals Configurations Direction of arrival Engineering Fourier transforms Frequency modulation Intelligence gathering Linear arrays Music Mutual coupling Parameter estimation Radar imaging Sensor arrays Sensors Signal detection Signal processing Target detection |
| Title | High resolution beam-forming for wide-band LFM chirps using super nested arrays |
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