Signal Processing for Novel Noise Radar Based on de-chirp and Delay Matching

Modern radar technology requires high-quality signals and detection performance. However, traditional frequency-modulated continuous wave (FMCW) radar often has poor anti-jamming capabilities, and the high sampling rates associated with large time-bandwidth product signals can lead to increased system hardware costs and reduced data processing efficiency. This paper constructed a composite radar waveform based on noise frequency modulation (NFM) and linear frequency modulation (LFM) signals, enhancing the signal's complexity and anti-jamming capability. Furthermore, a method for optimizing the processing of echo signals based on de-chirp and delay matching is proposed. The locally generated LFM signal is used to de-chirp the received echoes, resulting in a narrowband difference frequency noise signal. Subsequently, delay matching is performed in the fast time domain using the locally generated NFM signal according to the number of sampling points in the traversal processing period, allowing for the acquisition of target delay information. While reducing the analog-to-digital (A/D) sampling rate, the detection performance for wideband echo signals under high sampling rates is still maintained, with sidelobe levels and range resolution preserved. Accumulating this information in the slow time domain enables accurate target detection. The effectiveness of the proposed method is validated through simulation experiments.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2024-11-08
DOI
https://doi.org/10.3390/s24227169
Citations
2
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
2.60

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Signal Processing for Novel Noise Radar Based on de-chirp and Delay Matching

Zheng Dai, Ke Tan, Xingyu Lu, Jianchao Yang et al.
2 citations
Sensors
Radar Systems and Signal Processing
2.60
article

Signal Processing for Novel Noise Radar Based on de-chirp and Delay Matching

Zheng Dai, Ke Tan, Xingyu Lu, Jianchao Yang, Shiyuan Zhang, Xiaolin Cao, Hong Gu
article en
2 citations

Abstract

Modern radar technology requires high-quality signals and detection performance. However, traditional frequency-modulated continuous wave (FMCW) radar often has poor anti-jamming capabilities, and the high sampling rates associated with large time-bandwidth product signals can lead to increased system hardware costs and reduced data processing efficiency. This paper constructed a composite radar waveform based on noise frequency modulation (NFM) and linear frequency modulation (LFM) signals, enhancing the signal's complexity and anti-jamming capability. Furthermore, a method for optimizing the processing of echo signals based on de-chirp and delay matching is proposed. The locally generated LFM signal is used to de-chirp the received echoes, resulting in a narrowband difference frequency noise signal. Subsequently, delay matching is performed in the fast time domain using the locally generated NFM signal according to the number of sampling points in the traversal processing period, allowing for the acquisition of target delay information. While reducing the analog-to-digital (A/D) sampling rate, the detection performance for wideband echo signals under high sampling rates is still maintained, with sidelobe levels and range resolution preserved. Accumulating this information in the slow time domain enables accurate target detection. The effectiveness of the proposed method is validated through simulation experiments.

SensorsVol. 24(22)
Nanjing University of Science and Technology (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province, Nanjing University of Science and Technology, Nanjing University
Openalex Percentile: Top 8%
Radar Systems and Signal Processing
2.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.