4.7 Article

Deterministic Array Configurations for Radiometric Sensitivity Optimization in Microwave Interferometric Radiometers

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2021.3068143

关键词

Sensitivity; Microwave radiometry; Sensor arrays; Redundancy; Antenna measurements; Geometry; Reliability; Deterministic method; low-degradation linear array (LDLA); microwave interferometric radiometer (MIR); radiometric sensitivity; system reliability

资金

  1. National Natural Science Foundation of China [61901244, 61901242, 41706204]
  2. China Postdoctoral Science Foundation [2019M660643, 2019M660640, 2020T130338]

向作者/读者索取更多资源

This article proposes a deterministic method for designing low-degradation linear arrays, which takes advantage of the multiple-fold redundancy property of interferometric arrays' baseline coverage. The method can achieve satisfactory radiometric sensitivity with significantly low computational complexity.
Radiometric sensitivity is crucially important for microwave interferometric radiometers. To pursue optimum performance of radiometric sensitivity, the minimum-degradation arrays (MDAs) or low-degradation arrays (LDAs) are usually employed. In this article, we propose a deterministic method for designing low-degradation linear arrays (LDLAs), which exploits the multiple-fold redundancy property of baseline coverage (i.e., u-v coverage) of interferometric arrays and further devises analytical patterns for closed-form geometric construction. The proposed method can not only attain LDLAs with satisfactory radiometric sensitivity in significantly low computational complexity, given any number of sensor elements, but also has easy adoption on large array synthesis and configuration expansion scenarios. In addition, such analytically designed LDLAs also have the advantage of array robustness (or system reliability) in the sense of u-v coverage shrinking and ``hole'' occurrence (resulted from sensor failures). Numerical results are given to demonstrate the effectiveness of the proposed LDLA design method through comparison with stochastic algorithms based on heuristic search and combinatorial approaches uniting specific integer sequences, e.g., cyclic difference sets.

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