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- W2979589916 abstract "Accurate antenna motion-measurement is an essential pre-condition for synthetic aperture radar (SAR) to produce well-focused images. The measurement accuracy at high and low frequencies affects the quality of images and the geolocation error. Hence, motion compensation and focusing techniques require a minimum degree of accuracy in the radar motion measurements. The Inertial Measurement Unit (IMU) sensor selection process is done based on the SAR parametric requirements. The IMU instruments have inherent limited precision and accuracy, which are significantly related to the technology and the cost. The navigation algorithm may improve the precision and accuracy to overcome the limitations of the IMU sensor. This study intends to improve motion measurement accuracy using frequency-weighted state estimation. The proposed algorithm shows an error reduction in state estimation and an improvement in some parameter indices which are in relation to SAR image quality and geolocation. Two innovative algorithms are proposed in this study. The first one is the frequency-weighted Kalman filter which is an improved form of the Kalman filter. Another one is multi-resolution decomposition which is an approach to evaluate the SAR motion measurement system." @default.
- W2979589916 created "2019-10-18" @default.
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- W2979589916 date "2020-01-01" @default.
- W2979589916 modified "2023-10-18" @default.
- W2979589916 title "Accuracy improvement in motion‐measurement using frequency‐weighted Kalman filter" @default.
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- W2979589916 doi "https://doi.org/10.1049/iet-rsn.2019.0249" @default.
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