Sparse Detection in the Chirplet Transform: Application to FMCW Radar Signals

Millioz, Fabien; Davies, Michael

doi:10.1109/tsp.2012.2190730

Cited by 49 publications

(22 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Direct or indirect acquisition of high-quality and stable radar signals is the main research focus of researchers [171][172][173]. Radar signal, as a special signal, has opened up new research fields and methods for meteorology, exploration, flight, and autopilot and even opened up new horizons [174][175][176]. In this review, the design and classification of the radar signal are introduced by this paper primarily to reflect signal's differences and advantages according to radar signal respective characteristics.…”

Section: Resultsmentioning

confidence: 99%

Processing Technology Based on Radar Signal Design and Classification

Zhang

Zhan

2020

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

It is well known that the application of radar is becoming more and more popular with the development of the signal technology progress. This paper lists the current radar signal research, the technical progress achieved, and the existing limitations. According to radar signal respective characteristics, the design and classification of the radar signal are introduced to reflect signal’s differences and advantages. The multidisciplinary processing technology of the radar signal is classified and compared in details referring to adaptive radar signal process, pulse signal management, digital filtering signal mode, and Doppler method. The transmission process of radar signal is summarized, including the transmission steps of radar signal, the factors affecting radar signal transmission, and radar information screening. The design method of radar signal and the corresponding signal characteristics are compared in terms of performance improvement. Radar signal classification method and related influencing factors are also contrasted and narrated. Radar signal processing technology is described in detail including multidisciplinary technology synthesis. Adaptive radar signal process, pulse compression management, and digital filtering Doppler method are very effective technical means, which has its own unique advantages. At last, the future research trends and challenges of technologies of the radar signals are proposed. The conclusions obtained are beneficial to promote the further promotion applications both in theory and practice. The study work of this paper will be useful for choosing more reasonable radar signal processing technology methods.

show abstract

Section: Resultsmentioning

confidence: 99%

Processing Technology Based on Radar Signal Design and Classification

Zhang

Zhan

2020

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

show abstract

“…Which TF transform best fits to the ESM signals, e.g. an overcomplete transform like Chirplet [20], is also left for the future.…”

Section: Resultsmentioning

confidence: 99%

A low-complexity sub-Nyquist sampling system for wideband Radar ESM receivers

Yaghoobi

Lexa

Millioz

et al. 2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

View full text Add to dashboard Cite

The problem of efficient sampling of wideband Radar signals for Electronic Support Measures (ESM) is investigated in this paper. Wideband radio frequency sampling generally needs a sampling rate at least twice the maximum frequency of the signal, i.e. Nyquist rate, which is generally very high. However, when the signal is highly structured, like wideband Radar signals, we can use the fact that signals do not occupy the whole spectrum and instead, there exists a parsimonious structure in the time-frequency domain. Here, we use this fact and introduce a novel low complexity sampling system, which has a recovery guarantee, assuming that received RF signals follow a particular structure. The proposed technique is inspired by the compressive sampling of sparse signals and it uses a multi-coset sampling setting, however it does not involve a computationally expensive reconstruction step. We call this here Low-Complexity Multi-Coset (LoCoMC) sampling technique. Simulation results, show that the proposed sub-Nyquist sampling technique works well in simulated ES scenarios.

show abstract

“…The difference will be more important when the window has high-frequency components, e.g. Chirp let window [16]. A diagram which demonstrates the process of combining DFD filter and TF filter is shown in Figure 3.…”

Section: Yl[n]mentioning

confidence: 99%

An efficient implementation of the low-complexity multi-coset sub-Nyquist wideband radar electronic surveillance

Yaghoobi

Mulgrew

Davies

2014

2014 Sensor Signal Processing for Defence (SSPD)

View full text Add to dashboard Cite

The problem of' efficient sampling of' wide band radar signals f'or Electronic Surveillance (ES) using a parallel sampling structure will be investigated in this paper. Wide band radio frequency sampling, which is a necessary component of the modern digital radar surveillance systems, needs a sampling rate at least twice the maximum frequency of signals, i.e. Nyquist rate, which is generally very high. Designing an analog to digital converter which works with such a high sampling rate is difficult and expensive. The standard wide band ES receivers use the rapidly swept superheterodyne technique, which selects a sub band of the spectrum at a time, while iterating through the whole spectrum sequentially. Such a technique does not explore the underlying structure of' input RF signals. When the signal is sparsely structured, we can use the fact that signals do not occupy the whole spectrum. There indeed exists a parsimonious structure in the time-frequency domain in radar ES signals.We here use a recently introduced low-complexity sampling system, called LoCoMC [1], which is inspired by the compressive sampling (CS) of sparse signals and it uses the multi-coset sampling structure, while it does not involve a computationally expensive reconstruction step. A new implementation technique is here introduced, which further reduces the computational cost of the reconstruction algorithm by combining two filters, while improving the accuracy by implicitly implementing an infinite length filter.We also describe the rapidly swept superheterodyne receiver and compare it with the LoCoMC algorithm. In a contrast to the former technique, LoCoMC continuously monitors the spectrum, which makes it much more robust in the short pulse detection.

show abstract

Sparse Detection in the Chirplet Transform: Application to FMCW Radar Signals

Cited by 49 publications

References 11 publications

Processing Technology Based on Radar Signal Design and Classification

Processing Technology Based on Radar Signal Design and Classification

A low-complexity sub-Nyquist sampling system for wideband Radar ESM receivers

An efficient implementation of the low-complexity multi-coset sub-Nyquist wideband radar electronic surveillance

Contact Info

Product

Resources

About