Separate Estimation of Angular Velocity and Angle for Digital Array Radar

In this paper, we propose a method that enables one-dimensional estimation of angular velocity of a high-speed target by adding preprocessing to a received signal of a digital array radar. The proposed method enables two separate one-dimensional parameter estimations of angular velocity and angle, as opposed to the conventional method using two-dimensional searches. By one-dimensionalizing, both parameters can be calculated using monopulse principles, reducing the computational scale to approximately 1/1000 to 1/10,000 that of the conventional method. Meanwhile, computer simulation evaluations confirmed that the proposed method is better than the conventional method in terms of parameter estimation accuracy at a signal to noise power ratio (SNR) of around 15 dB, and it approaches the Cramer-Rao lower bound at high SNRs.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10890075
Primary Topic
Advanced SAR Imaging Techniques
Type
article
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article

Separate Estimation of Angular Velocity and Angle for Digital Array Radar

Tsubasa Terada, Ryuhei Takahashi, Toshihiro Ito
Advanced SAR Imaging Techniques
article

Separate Estimation of Angular Velocity and Angle for Digital Array Radar

Tsubasa Terada, Ryuhei Takahashi, Toshihiro Ito
article en

Abstract

In this paper, we propose a method that enables one-dimensional estimation of angular velocity of a high-speed target by adding preprocessing to a received signal of a digital array radar. The proposed method enables two separate one-dimensional parameter estimations of angular velocity and angle, as opposed to the conventional method using two-dimensional searches. By one-dimensionalizing, both parameters can be calculated using monopulse principles, reducing the computational scale to approximately 1/1000 to 1/10,000 that of the conventional method. Meanwhile, computer simulation evaluations confirmed that the proposed method is better than the conventional method in terms of parameter estimation accuracy at a signal to noise power ratio (SNR) of around 15 dB, and it approaches the Cramer-Rao lower bound at high SNRs.

Mitsubishi Electric (Japan) (JP)
Affordable and clean energy
Openalex Percentile: Top 94%
Advanced SAR Imaging Techniques
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