Abstract

Sparse sensor arrays can match the performance of fully populated arrays using substantially fewer elements. However, finding the array configuration with the smallest number of elements is generally a computationally difficult problem. Consequently, simple to generate array configurations that may be suboptimal are of high practical interest. This paper presents a novel closed-form sparse linear array configuration designed for active sensing, called the Concatenated Nested Array (CNA). The key parameters of the CNA are derived. The CNA is also compared to the optimal Minimum-Redundancy Array (MRA) in numerical simulations. The CNA is shown to require only about 10% more elements than the MRA in the limit of large apertures.

Highlights

  • Phased sensor arrays are a critical technology in many application areas including radar, wireless communication, medical imaging, radio astronomy, sonar and seismology [1]

  • This paper presents a novel closed-form sparse linear array configuration designed for active sensing, called the Concatenated Nested Array (CNA)

  • The CNA is compared to the optimal Minimum-Redundancy Array (MRA) in numerical simulations

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Summary

INTRODUCTION

Phased sensor arrays are a critical technology in many application areas including radar, wireless communication, medical imaging, radio astronomy, sonar and seismology [1]. Finding optimal sparse array geometries, such as the Minimum-Redundancy Array (MRA) [9], is generally a computationally hard problem, with no known polynomial time solution. This has led to the development of several suboptimal, but mathematically tractable array configurations [5], [8], [10]–[12]. The number of elements N in these Reduced Redundancy Arrays (RRA√s) scales linearly with aperture L, generally N ∝ L should be achievable.

Sparse arrays and the co-array
Postage stamp problem
Figures of merit of sparse arrays
Sparse array configurations
Array design
Solution to relaxed problem
General solution
NUMERICAL RESULTS
CONCLUSION

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