Enabling Real-Time Imaging and Onboard RFI Localization for Three-Level Quantized Microwave Interferometric Radiometers.
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| Title: | Enabling Real-Time Imaging and Onboard RFI Localization for Three-Level Quantized Microwave Interferometric Radiometers. |
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| Authors: | Zhang, Ziyang1,2 (AUTHOR), Liu, Hao1,2 (AUTHOR) liuhao@mirslab.cn, Han, Donghao1 (AUTHOR), Tong, Xing1,2 (AUTHOR), Lu, Hao1 (AUTHOR), Huo, Changxing1 (AUTHOR) |
| Source: | Remote Sensing. Jun2026, Vol. 18 Issue 11, p1734. 19p. |
| Subjects: | Brightness temperature, Radio interference, Estimation theory, Signal quantization, Microwave radiometers, Optimization algorithms, Electronic data processing, Image reconstruction |
| Abstract: | Highlights: What are the main findings? Real-time brightness temperature (TB) reconstruction for microwave interferometric radiometers (MIRs) is achieved through the development of fast estimation algorithms for the normalized three-level quantization threshold. An onboard real-time data processing framework is established for three-level quantization MIRs, enabling real-time TB imaging and radio frequency interference (RFI) localization based on real-time reconstructed TB images. What is the implication of the main finding? Microwave interferometric radiometers with real-time imaging capability can significantly improve in-orbit intelligent observation performance, particularly for onboard RFI processing, information extraction, and fusion. This also enables new application scenarios, such as an alternative vision under degraded visual environments (DVE). Real-time imaging processing for microwave interferometric radiometer (MIR) has great potential in various application fields, such as onboard data processing, onboard information fusion, and alternative visual applications. The primary challenge lies in the computational complexity of the entire processing chain, including both visibility function preprocessing and brightness temperature (TB) reconstruction. In this study, the real-time estimation of the normalized threshold level is identified as the key step for enabling real-time imaging of three-level quantized MIR systems. Three algorithms—Acklam's algorithm (AKA), polynomial fitting algorithm (PFA), and Taylor expansion algorithm (TEA)—are proposed and evaluated. The PFA provides a favorable balance between estimation accuracy and computational efficiency. Leveraging the proposed algorithms, this paper further establishes an onboard real-time processing framework for three-level quantization MIRs, enabling real-time TB imaging and radio frequency interference (RFI) localization. A real-time imaging experiment was carried out with a 15-element, 50 GHz one-dimensional MIR system, which demonstrates real-time imaging of fast-moving vehicles on the expressway with greatly reduced computational latency (an imaging time of 570.9 μs for 159 baselines). A further flight experiment employing an L-band system verifies the feasibility of onboard RFI localization, and the proposed real-time RFI localization method shows an average angular deviation of 0.32° with respect to an offline MUSIC estimator, corresponding to 2.1% of the nominal spatial resolution. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? Real-time brightness temperature (TB) reconstruction for microwave interferometric radiometers (MIRs) is achieved through the development of fast estimation algorithms for the normalized three-level quantization threshold. An onboard real-time data processing framework is established for three-level quantization MIRs, enabling real-time TB imaging and radio frequency interference (RFI) localization based on real-time reconstructed TB images. What is the implication of the main finding? Microwave interferometric radiometers with real-time imaging capability can significantly improve in-orbit intelligent observation performance, particularly for onboard RFI processing, information extraction, and fusion. This also enables new application scenarios, such as an alternative vision under degraded visual environments (DVE). Real-time imaging processing for microwave interferometric radiometer (MIR) has great potential in various application fields, such as onboard data processing, onboard information fusion, and alternative visual applications. The primary challenge lies in the computational complexity of the entire processing chain, including both visibility function preprocessing and brightness temperature (TB) reconstruction. In this study, the real-time estimation of the normalized threshold level is identified as the key step for enabling real-time imaging of three-level quantized MIR systems. Three algorithms—Acklam's algorithm (AKA), polynomial fitting algorithm (PFA), and Taylor expansion algorithm (TEA)—are proposed and evaluated. The PFA provides a favorable balance between estimation accuracy and computational efficiency. Leveraging the proposed algorithms, this paper further establishes an onboard real-time processing framework for three-level quantization MIRs, enabling real-time TB imaging and radio frequency interference (RFI) localization. A real-time imaging experiment was carried out with a 15-element, 50 GHz one-dimensional MIR system, which demonstrates real-time imaging of fast-moving vehicles on the expressway with greatly reduced computational latency (an imaging time of 570.9 μs for 159 baselines). A further flight experiment employing an L-band system verifies the feasibility of onboard RFI localization, and the proposed real-time RFI localization method shows an average angular deviation of 0.32° with respect to an offline MUSIC estimator, corresponding to 2.1% of the nominal spatial resolution. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18111734 |
