Segmented Radon Fourier Transform for Long Time Coherent Radars

Coherent pulse integration is a well-known technique for effective target detection with increased output signal-to-noise ratio (SNR). Radon fourier transform (RFT) uses long-time coherent integration technique for improved target detection in a 3-dimensional search but increases the parameters sear...

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Bibliographic Details
Published in:IEEE sensors journal 2023-05, Vol.23 (9), p.1-1
Main Authors: Hussain, Musadiq, Ahmed, Rehan, Cheema, Hammad M.
Format: Article
Language:English
Subjects:
Computational cost
Discrete Radon Fourier Transform
Fourier transforms
long-time coherent integration
Microprocessors
Object detection
Parallel processing
Parameters
Radar
Radar cross-sections
Radar receivers
Radon
Searching
Segmented Radon Fourier Transform
Segments
Sensors
Signal to noise ratio
SRFT
Target detection
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Summary:Coherent pulse integration is a well-known technique for effective target detection with increased output signal-to-noise ratio (SNR). Radon fourier transform (RFT) uses long-time coherent integration technique for improved target detection in a 3-dimensional search but increases the parameters search time. This paper presents a new approach of Segmented Radon Fourier Transform (SRFT) for fast detection of high speed targets without significantly degrading the detection performance. SRFT divides the received echo data matrix into an arbitrary number of segments along the slow time dimension of the data matrix. Each segment is a complete independent data matrix which can proceed independently and in parallel fashion. This paper implements a complete pipeline of radar receiver with SRFT to validate its integration in a radar signal processor. Experiments show that the parameters search time of SRFT is reduced by N k times when compared with RFT, where N k is the number of segments. There is a negligible degradation of 0.035dB in SNR when compared with standard RFT for 120 pulses. The difference is further reduced as the number of pulses are increased.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3260024