The realization of the parameter estimation of chirp signals using the fractional Fourier transform （FRFT） is based on the assumption that the sampling duration of practical observed signals would be equal to the ti...The realization of the parameter estimation of chirp signals using the fractional Fourier transform （FRFT） is based on the assumption that the sampling duration of practical observed signals would be equal to the time duration of chirp signals contained in the former. However, in many actual circumstances, this assumption seems unreasonable. On the basis of analyzing the practical signal form, this paper derives the estimation error of the existing parameter estimation method and then proposes a novel and universal parameter estimation algorithm. Furthermore, the proposed algorithm is developed which allows the estimation of the practical observed Gaussian windowed chirp signal. Simulation results show that the new algorithm works well.展开更多
To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband ...To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.展开更多
A novel M-ary chirp modulation technique based on an optimal chirp signal design is proposed in this paper to offer higher data rate for an indoor wireless chirp spread spectrum communication system. Both linear chirp...A novel M-ary chirp modulation technique based on an optimal chirp signal design is proposed in this paper to offer higher data rate for an indoor wireless chirp spread spectrum communication system. Both linear chirp signals and combined chirp signals are used in this system to reduce the effect of the cross correlation, and simplify the complexity of the system. The optimal scheme of de- signing both linear chirp signals and combined chirp signals is discussed to minimize the value of the cross correlation and obtain a better system performance. Simulation results show that, compared with the binary orthogonal chirp modulation technique, the M-ary chirp modulation technique based on an optimal chirp signal set has a higher data rate with a reasonable bit-error rate （BER） perform- ance under both additive white gaussian noise （AWGN） channel and indoor wireless channel.展开更多
Chirp signals show energy aggregation in the fractional Fourier domain(FrFD) w hich can be used to estimate the parameter of the signals. In this paper,a parameter estimation method for multi-component chirp signal w ...Chirp signals show energy aggregation in the fractional Fourier domain(FrFD) w hich can be used to estimate the parameter of the signals. In this paper,a parameter estimation method for multi-component chirp signal w hich corrupted by w hite Gaussian noise is proposed based on the discrete fractional Fourier transform(DFrFT) and the differential evolution( DE) algorithm. The proposed algorithm uses the DE algorithm instead of the conventional fine search algorithm to detect the peak of the signals in the FrFD. The paper simulated the influence of the noise and the resolution of the proposed algorithm. The results of the simulation show the proposed method does not only improve the estimation accuracy of the peak coordinate,but also reduces time consuming.展开更多
To prevent the long-time coherent integration and limited range window stumbling blocks of stretch processing and reduce computational complexity, a novel method called multi-subpulse process of large time-bandwidth p...To prevent the long-time coherent integration and limited range window stumbling blocks of stretch processing and reduce computational complexity, a novel method called multi-subpulse process of large time-bandwidth product linear frequency modulating （ LFM ） signal （ i. e. chirp ） is proposed in this paper. The wideband chirp signal is split up into several compressed subpulses. Then the fast Fourier transform （FFT） is used to reconstruct the high resolution range profile （ HR- RP） in a relative short computation time. For multi-frame, pulse Doppler （PD） process is performed to obtain the two-dimension range-Doppler （R-D） high resolution profile. Simulations and field ex- perimental results show that the proposed method can provide high-quality target profile over a large range window in a short computation time and has the promising potential for long-time coherent in- tegration.展开更多
A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate t...A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate the 1F of a multi-component Chirp signal accurately. Wigner distribution maxima （WDM） are usually utilized for this estimation. But in practice, estimation bias increases when some points deviate from the true IF in high noise environments. This paper presents a new method of multi-component Chirp signal 1F estimation named Wigner Viterbi fit （WVF）, based on Wigner-Ville distribution （WVD） and the Viterbi algorithm. First, we transform the WVD of the Chirp signal into digital image, and apply the Viterbi algorithm to separate the components and estimate their IF. At last, we establish a linear model to fit the estimation results. Theoretical analysis and simulation results prove that this new method has high precision and better performance than WDM in high noise environments, and better suppression of interference and the edge effect. Compared with WDM, WVF can reduce the mean square error （MSE） by 50% when the signal to noise ration （SNR） is in the range of-15dB to -11dB. WVF is an effective and promising 1F estimation method.展开更多
Stepped frequency chirp signal obtains high-resolution radar images by synthesizing multiple narrowband chirp pulses.It has been one of the most commonly used wideband radar waveforms due to its lower demand for radar...Stepped frequency chirp signal obtains high-resolution radar images by synthesizing multiple narrowband chirp pulses.It has been one of the most commonly used wideband radar waveforms due to its lower demand for radar instant bandwidth.In this paper,we propose a radar jamming method using two-dimensional nonperiodic phase modulation against stepped frequency chirp signal imaging radar.Using the unique property of nonperiodic phase modulation,the proposed method can generate high-level sidelobes that perform as a special blanket jamming along both the range and azimuth directions and make the target unrecognizable.Then,the influence of different modulation parameters,such as the code width and duty ratio,are further discussed.Based on this,the corresponding parameter design principles are presented.Finally,the validity of the proposed method is demonstrated by the Yake-42 plane data simulation and measured unmanned aerial vehicle data experiment.展开更多
Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-compone...Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.展开更多
Higher order statistical features have been recently proved to be very efficient in the classification of wideband communications and radar signals with great accuracy. On the other hand, the denoising properties of t...Higher order statistical features have been recently proved to be very efficient in the classification of wideband communications and radar signals with great accuracy. On the other hand, the denoising properties of the wavelet transform make WT an efficient signal processing tool in noisy environments. A novel technique for the classification of multi-user chirp modulation signals is presented in this paper. A combination of the higher order moments and cumulants of the wavelet coefficients as well as the peaks of the bispectrum and its bi-frequencies are proposed as effective features. Different types of artificial intelligence based classifiers and clustering techniques are used to identify the chirp signals of the different users. In particular, neural networks (NN), maximum likelihood (ML), k-nearest neighbor (KNN) and support vector machine (SVMs) classifiers as well as fuzzy c-means (FCM) and fuzzy k-means (FKM) clustering techniques are tested. The Simulation results show that the proposed technique is able to efficiently classify the different chirp signals in additive white Gaussian noise (AWGN) channels with high accuracy. It is shown that the NN classifier outperforms other classifiers. Also, the simulations prove that the classification based on features extracted from wavelet transform results in more accurate results than that using features directly extracted from the chirp signals, especially at low values of signal-to-noise ratios.展开更多
基金supported by the National Natural Science Foundation of China (60872003 61071214)+1 种基金the Doctoral Fund of Ministry of Education of China (20093201110005)the Foundation of Chinese National Defense Technology Key Laboratory (9140C1301031001)
文摘The realization of the parameter estimation of chirp signals using the fractional Fourier transform （FRFT） is based on the assumption that the sampling duration of practical observed signals would be equal to the time duration of chirp signals contained in the former. However, in many actual circumstances, this assumption seems unreasonable. On the basis of analyzing the practical signal form, this paper derives the estimation error of the existing parameter estimation method and then proposes a novel and universal parameter estimation algorithm. Furthermore, the proposed algorithm is developed which allows the estimation of the practical observed Gaussian windowed chirp signal. Simulation results show that the new algorithm works well.
文摘To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.
文摘A novel M-ary chirp modulation technique based on an optimal chirp signal design is proposed in this paper to offer higher data rate for an indoor wireless chirp spread spectrum communication system. Both linear chirp signals and combined chirp signals are used in this system to reduce the effect of the cross correlation, and simplify the complexity of the system. The optimal scheme of de- signing both linear chirp signals and combined chirp signals is discussed to minimize the value of the cross correlation and obtain a better system performance. Simulation results show that, compared with the binary orthogonal chirp modulation technique, the M-ary chirp modulation technique based on an optimal chirp signal set has a higher data rate with a reasonable bit-error rate （BER） perform- ance under both additive white gaussian noise （AWGN） channel and indoor wireless channel.
文摘Chirp signals show energy aggregation in the fractional Fourier domain(FrFD) w hich can be used to estimate the parameter of the signals. In this paper,a parameter estimation method for multi-component chirp signal w hich corrupted by w hite Gaussian noise is proposed based on the discrete fractional Fourier transform(DFrFT) and the differential evolution( DE) algorithm. The proposed algorithm uses the DE algorithm instead of the conventional fine search algorithm to detect the peak of the signals in the FrFD. The paper simulated the influence of the noise and the resolution of the proposed algorithm. The results of the simulation show the proposed method does not only improve the estimation accuracy of the peak coordinate,but also reduces time consuming.
基金Supported by the National Natural Science Foundation of China(61301189)
文摘To prevent the long-time coherent integration and limited range window stumbling blocks of stretch processing and reduce computational complexity, a novel method called multi-subpulse process of large time-bandwidth product linear frequency modulating （ LFM ） signal （ i. e. chirp ） is proposed in this paper. The wideband chirp signal is split up into several compressed subpulses. Then the fast Fourier transform （FFT） is used to reconstruct the high resolution range profile （ HR- RP） in a relative short computation time. For multi-frame, pulse Doppler （PD） process is performed to obtain the two-dimension range-Doppler （R-D） high resolution profile. Simulations and field ex- perimental results show that the proposed method can provide high-quality target profile over a large range window in a short computation time and has the promising potential for long-time coherent in- tegration.
基金Supported by the National Natural Science Foundation of China under Grant No. 60572098.
文摘A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate the 1F of a multi-component Chirp signal accurately. Wigner distribution maxima （WDM） are usually utilized for this estimation. But in practice, estimation bias increases when some points deviate from the true IF in high noise environments. This paper presents a new method of multi-component Chirp signal 1F estimation named Wigner Viterbi fit （WVF）, based on Wigner-Ville distribution （WVD） and the Viterbi algorithm. First, we transform the WVD of the Chirp signal into digital image, and apply the Viterbi algorithm to separate the components and estimate their IF. At last, we establish a linear model to fit the estimation results. Theoretical analysis and simulation results prove that this new method has high precision and better performance than WDM in high noise environments, and better suppression of interference and the edge effect. Compared with WDM, WVF can reduce the mean square error （MSE） by 50% when the signal to noise ration （SNR） is in the range of-15dB to -11dB. WVF is an effective and promising 1F estimation method.
基金Project supported by the Natural Science Foundation of Hunan Province,China(No.2022JJ40561)the Scientific Research Program of National University of Defense Technology,China(No.ZK22-46)the National Natural Science Foundation of China(Nos.61890542,62001481,and 62071475)。
文摘Stepped frequency chirp signal obtains high-resolution radar images by synthesizing multiple narrowband chirp pulses.It has been one of the most commonly used wideband radar waveforms due to its lower demand for radar instant bandwidth.In this paper,we propose a radar jamming method using two-dimensional nonperiodic phase modulation against stepped frequency chirp signal imaging radar.Using the unique property of nonperiodic phase modulation,the proposed method can generate high-level sidelobes that perform as a special blanket jamming along both the range and azimuth directions and make the target unrecognizable.Then,the influence of different modulation parameters,such as the code width and duty ratio,are further discussed.Based on this,the corresponding parameter design principles are presented.Finally,the validity of the proposed method is demonstrated by the Yake-42 plane data simulation and measured unmanned aerial vehicle data experiment.
基金Sponsored by the National Natural Science Foundation of China (60232010 ,60572094)the National Science Foundation of China for Distin-guished Young Scholars (60625104)
文摘Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.
文摘Higher order statistical features have been recently proved to be very efficient in the classification of wideband communications and radar signals with great accuracy. On the other hand, the denoising properties of the wavelet transform make WT an efficient signal processing tool in noisy environments. A novel technique for the classification of multi-user chirp modulation signals is presented in this paper. A combination of the higher order moments and cumulants of the wavelet coefficients as well as the peaks of the bispectrum and its bi-frequencies are proposed as effective features. Different types of artificial intelligence based classifiers and clustering techniques are used to identify the chirp signals of the different users. In particular, neural networks (NN), maximum likelihood (ML), k-nearest neighbor (KNN) and support vector machine (SVMs) classifiers as well as fuzzy c-means (FCM) and fuzzy k-means (FKM) clustering techniques are tested. The Simulation results show that the proposed technique is able to efficiently classify the different chirp signals in additive white Gaussian noise (AWGN) channels with high accuracy. It is shown that the NN classifier outperforms other classifiers. Also, the simulations prove that the classification based on features extracted from wavelet transform results in more accurate results than that using features directly extracted from the chirp signals, especially at low values of signal-to-noise ratios.
