MIMO Radar Ambiguity Properties and Optimization Using Frequency-Hopping Waveforms

Chen, Chun-Yang; Vaidyanathan, P.P.

doi:10.1109/tsp.2008.929658

Cited by 235 publications

(20 citation statements)

References 30 publications

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“…In [31], the classical ambiguity function is expanded to the MIMO radar case. And in [32], properties of MIMO radar ambiguity functions are invesigated.…”

Section: Literature Overviewmentioning

confidence: 99%

Target localization methods for frequency-only MIMO radar

Kalkan

Baykal

2010

2010 IEEE 18th Signal Processing and Communications Applications Conference

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“…In [31], the classical ambiguity function is expanded to the MIMO radar case. And in [32], properties of MIMO radar ambiguity functions are invesigated.…”

Section: Literature Overviewmentioning

confidence: 99%

Target localization methods for frequency-only MIMO radar

Kalkan

Baykal

2010

2010 IEEE 18th Signal Processing and Communications Applications Conference

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“…San Antonio and Fuhrmann discussed some properties of the MIMO radar ambiguity function, which provide several ideas for MIMO waveform optimization [17]. The frequency-hopping (FH) sequences presented in [18] were used in MIMO radar configuration [19,20]. The FH orthogonal transmit waveforms discussed in [18] are initially considered for multiuser radar system.…”

Section: Introductionmentioning

confidence: 99%

“…The frequency-hopping (FH) sequences presented in [18] were used in MIMO radar configuration [19,20]. The FH orthogonal transmit waveforms discussed in [18] are initially considered for multiuser radar system. Furthermore, [18] employed the FH codes to minimize the peaks in the cross correlation functions of the transmit waveforms as much as possible.…”

Section: Introductionmentioning

confidence: 99%

Cognitive Frequency-Hopping Waveform Design for Dual-Function MIMO Radar-Communications System

Yao

2020

Sensors

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A frequency-hopping (FH)-based dual-function multiple-input multiple-output (MIMO) radar communications system enables implementation of a primary radar operation and a secondary communication function simultaneously. The set of transmit waveforms employed to perform the MIMO radar task is generated using FH codes. For each transmit antenna, the communication operation can be realized by embedding one phase symbol during each FH interval. However, as the radar channel is time-variant, it is necessary for a successive waveform optimization scheme to continually obtain target feature information. This research work aims at enhancing the target detection and feature estimation performance by maximizing the mutual information (MI) between the target response and the target returns, and then minimizing the MI between successive target-scattering signals. The two-step cognitive waveform design strategy is based upon continuous learning from the radar scene. The dynamic information about the target feature is utilized to design FH codes. Simulation results show an improvement in target response extraction, target detection probability and delay-Doppler resolution as the number of iterations increases, while still maintaining high data rate with low bit error rates between the proposed system nodes.

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“…Frequency hopping technology is an effective anti-jamming communication technology, it has wide applications in military communications and other civilian fields [1]- [5]. The carrier frequency of the frequency hopping radar signal is pseudo-randomly hopped with time, so FH radar signal has a high spectrum utilization rate.…”

Section: Introductionmentioning

confidence: 99%

Robust Multi-Frame Joint Frequency Hopping Radar Waveform Parameters Estimation Under Low Signal-Noise-Ratio

et al. 2019

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Robust estimation of frequency hopping radar signal parameters is the key to achieving stable jam in frequency hopping communication. In order to deal with the poor noise resistance performance of conventional time-frequency analysis based parameter estimation method under low signal-noise-ratio conditions. A robust method is proposed in this paper for frequency hopping radar waveform parameters estimation. The method is performed in time domain. Firstly, the pulse repetition interval of the received radar signal is extracted by matching filtering, which is used as the window length to divide the signal into multiple frames. The coherent integration process is performed on the multi-frame signal to increase the signal-noise-ratio, which effectively ensures the robustness of the algorithm under low signal-noiseratio conditions. Secondly, the short-time Fourier transform is used to realize the rough estimation of the frequency hopping number, which reduces the range of subsequent hopping counts and reduces the amount of algorithm calculation. Finally, an accurate estimation of the waveform parameters including frequency hopping sequence, hop duration, frequency hopping interval and carrier frequency is realized. Simulation experiments verify the effectiveness of the algorithm and the robustness under various signal-noise-ratio conditions. INDEX TERMS Hopping frequency waveform, parameter estimation, multiple-frame, short time Fourier transform (STFT).

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MIMO Radar Ambiguity Properties and Optimization Using Frequency-Hopping Waveforms

Cited by 235 publications

References 30 publications

Target localization methods for frequency-only MIMO radar

Target localization methods for frequency-only MIMO radar

Cognitive Frequency-Hopping Waveform Design for Dual-Function MIMO Radar-Communications System

Robust Multi-Frame Joint Frequency Hopping Radar Waveform Parameters Estimation Under Low Signal-Noise-Ratio

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