Assessment of chaos-based FM signals for range–Doppler imaging

Flores, Benjamin C.; Solis, E.A.; Gabriel, Thomas

doi:10.1049/ip-rsn:20030728

Cited by 103 publications

(50 citation statements)

References 19 publications

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“…The CCM is generated by embedding a Logistic map into a Bernoulli map, which are shown in Table 1 [31]. The generation procedure of CCM is: 1) employ the Logistic map to generate the parameters for Bernoulli map; 2) combine the Bernoulli map sequences under different parameters to obtain the CCM sequence.…”

Section: Mapmentioning

confidence: 99%

Wide-Band Chaotic Noise Signal for Velocity Estimation and Imaging of High-Speed Moving Targets

Yang¹,

Zhang²,

Gu³

2015

PIER B

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Abstract-This paper proposes a burst model of chaotic noise signals with randomly stepped carrier frequencies for velocity estimation and high-resolution range imaging of high-speed moving targets. The random stepping of carrier frequencies is controlled by a combination chaotic map (CCM), which is generated by embedding a Logistic map into a Bernoulli map. The baseband noise signal adopts the CCM based frequency-modulation (CCM-FM) signal, which has good randomness and a thumbtack ambiguity function as well. The velocity estimation includes a coarse search and a precise search, where the coarse search is conducted with a fixed step to makes the velocity deviation less than the velocity resolution, while the precise search adopts the Golden Section Search (GSS) algorithm to get an accurate estimation of velocity. What should be emphasized is that the velocity estimation process can be completed with just a burst of subpulses. Then the spectra are coherently synthesized to obtain ultra-wide bandwidth and high-resolution range imaging. Finally, numerical simulations demonstrate a good performance of the proposed signal model and the processing algorithm.

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Section: Mapmentioning

confidence: 99%

Wide-Band Chaotic Noise Signal for Velocity Estimation and Imaging of High-Speed Moving Targets

Yang¹,

Zhang²,

Gu³

2015

PIER B

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“…Random noise radar is a kind of radar which transmits stochastic/pseudo-stochastic signals [5][6][7][8][9][10][11][12]. It has good performance on electronic counter countermeasure (ECCM) and very low probability of interception, as well as achieving approximately "thumbtack" ambiguity function [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…It has good performance on electronic counter countermeasure (ECCM) and very low probability of interception, as well as achieving approximately "thumbtack" ambiguity function [5,6]. Chaotic signal is one kind of pseudo-stochastic signals which has already been used in random noise radars [9][10][11][12]. In [10], point target imaging using chaotic FM signals was simulated.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Sparse Stepped Chaotic Signal and Its Compression Based on Compressive Sensing

Yang¹,

Zhang²

2013

PIER

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Abstract-We propose a novel signal model by combining the sparse stepped frequency signals with chaotic signals, i.e., the sparse stepped chaotic signal (SSCS) model, as well as the corresponding compression algorithm based on compressed sensing. In SSCS, the chaotic signals are modulated to sparse stepped frequencies to compose a transmitting burst. When receiving, the echo signals are demodulated to the baseband and then can be sampled directly at a rate much lower than the Nyquist rate determined by the bandwidth of chaotic signal of each subpulse. Compared with radars using conventional stepped frequency waveforms, the SSCS radar can transmit fewer subpulses in a burst and directly use lower speed ADC next to the receiver. Both simulated and real radar data are processed to demonstrate the effectiveness of the proposed SSCS as well as the compression algorithm by which high resolution range profiles are very well reconstructed.

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“…Recent studies have shown that fast chaotic dynamics can be used for a variety of applications such as information transmission with high power efficiency [1], generating truly random numbers [2,3], radar [4][5][6][7][8], as well as novel spread spectrum [9], ultrawide-bandwidth [10,11], and optical [12,13] communication schemes. In these applications, it is desirable to generate chaos in the fast regime where the typical time scale of the fluctuations is on the order of 1 ns or less [12,14].…”

Section: Introductionmentioning

confidence: 99%