Radar High-Speed Moving Target Coherent Integration and Parameter Estimation Algorithm Using PSA-FAIR-NUFFT

With the extension of signal accumulation time, high-speed and low-radar-cross-section (RCS) aerial vehicles cause serious range cell migration (RCM) and Doppler frequency migration (DFM) in radar echoes, significantly degrading radar detection performance. To address the challenge of weak target de...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE sensors journal Ročník 25; číslo 13; s. 24712 - 24730
Hlavní autori: Wang, Le, Tao, Haihong, Yang, Aodi, Yang, Fusen, Ma, Huihui
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.07.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Classification algorithms
Coherent integration (CI)
Data analysis
Doppler effect
Fast Fourier transformations
Fast Fourier transforms
Fourier transforms
Frequency domain analysis
High speed
Moving targets
nonuniform fast Fourier transform (NUFFT)
Parameter estimation
PID-based search algorithm (PSA)
Proportional integral derivative
Radar
Radar cross sections
Radar detection
Radar echoes
Rotation
Search algorithms
Search problems
Signal processing algorithms
Signal to noise ratio
Target acquisition
Target detection
Time-frequency analysis
Trajectory
ISSN:1530-437X, 1558-1748
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:With the extension of signal accumulation time, high-speed and low-radar-cross-section (RCS) aerial vehicles cause serious range cell migration (RCM) and Doppler frequency migration (DFM) in radar echoes, significantly degrading radar detection performance. To address the challenge of weak target detection, long-time coherent integration (LTCI) techniques enhance the signal-to-noise ratio (SNR) by concentrating energy in the time-frequency domain (TFD) or transform domain. However, existing LTCI methods primarily focus on acquiring the target's initial range parameters during the coherent integration interval (CPI), but neglecting potential distance deviation between the actual range and the initial range after the integration. This article proposes a novel LTCI algorithm, PSA-FAIR-NUFFT, combining frequency-domain angular inverse rotation (FAIR), nonuniform fast Fourier transform (NUFFT), and the proportional-integral-derivative (PID)-based search algorithm (PSA). The method effectively integrates signal energy and estimates final range parameters for moving targets. Specifically, FAIR establishes the frequency-domain axis rotation (AR) relationship to align the target trajectory into the final range unit. Concurrently, NUFFT performs coherent integration (CI) as well as the motion parameters estimation. To optimize the rotation angle search efficiency, an objective function based on the accumulated peak value is formulated with the PSA improving computational efficiency. This approach achieves precise parameter estimation with low complexity. Furthermore, for multitarget detection scenarios involving mixed-strength targets, a modified CLEAN technique is incorporated to sequentially separate strong and weak targets. Compared with typical LTCI algorithms, both numerical simulation experiments and real data analysis demonstrate the effectiveness and reliability of the proposed algorithm.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2025.3566076