Parameter estimation method for a linear frequency modulation signal with a Duffing oscillator based on frequency periodicity

In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.

NEW TYPE OF WINDOWS FOR DIGITAL PULSE COMPRESSION IN FREQUENCY DOMAIN FOR BROADBAND LFM SIGNALS

A new type of window called combined window is designed to get higher Ratio of Mainlobe to Sidelobes (RMS) and lower Mainlobe Widening Factor (MWF). Simulation results prove that the new window can solve the contradiction between RMS and MWF better than classic windows.

Parameter estimation of LFM signals based on time reversal

In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).

基于FRFT的低信噪比LFM信号参数快速估计算法

基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)对线性调频(Linear Frequency Modulated,LFM)信号参数进行估计,问题关键是确定FRFT最佳阶数,根据误差迭代思想提出新的参数估计算法,该算法利用归一化带宽和旋转角的转化关系,由估计误差推算角度差值,有效降低了运算量,不需要调频斜率正负的先验信息,改进的对数搜索算法可以进一步提高参数估计结果的稳定性和可靠性。仿真结果表明,信噪比在-8 dB以上时该方法在高效率的前提下仍具有良好的参数估计性能,平均估计误差在1%以内,估计结果接近Cramer-Rao下限,满足工程实时处理需求。

Simultaneous range and radial velocity estimation with a single narrowband LFM pulse

The mismatch effect induced by the radial motion of a target is analyzed for linear frequency modulated （LFM） signals. Then, a novel integrated processing scheme is proposed to re- solve the delay-Doppler coupling effect in LFM pulse compression. Therefore the range and radial velocity of the target can be si- multaneously estimated with a narrowband LFM pulse. Finally, numerical simulation results demonstrate the effectiveness and good performance of the proposed method.

脉冲噪声下基于DCNN的LFM信号去噪方法

由于脉冲噪声具有明显的尖峰脉冲特性,使得基于高斯假设的传统去噪方法无法有效滤除脉冲噪声。针对这个问题,文中提出了一种脉冲噪声下基于深度卷积神经网络(DCNN)的线性调频(LFM)信号去噪方法。首先,生成LFM信号和随机脉冲噪声,构建不同广义信噪比下的数据集,输入DCNN进行训练和测试。进而,从时域波形图、分数谱、时频分布三个方面验证模型的去噪能力。最后,对去噪LFM信号进行分数阶傅里叶变换,通过搜寻分数谱中的峰值点来估计LFM信号的参数。仿真实验结果表明,文中方法不仅能够有效去除含噪信号中的随机脉冲噪声,而且还可以保持LFM信号的时域特征、分数谱特征和时频特征基本不变,进而提高了参数估计的噪声鲁棒性。与传统的基于非线性变换的方法相比,本文方法在低信噪比下仍能有效保持信号的分数谱特征和时频特征,具有更好的去噪性能和泛化能力。

基于Z变换和改进FRI的LFM信号参数估计方法研究

为了完成线性调频(linear frequency modulation,LFM)信号的稀疏采样,并利用稀疏数据对原始信号参数进行估计,本文提出了一种基于Z变换和改进有限新息率(finite rate of innovation,FRI)的LFM信号参数估计方法。以Z变换理论为基础,设计了一种数学模型,一旦信号能够表达成该数学模型的结构形式,就能通过Z变换和零化滤波器的方法估计信号参数。然后,利用了自相关延迟的FRI结构对LFM信号采样,该结构不仅完成了LFM信号的稀疏采样,而且稀疏采样结果能够与数学模型结构相符。在理论上通过数学论证的方式证明了所提方法能够用于获取LFM信号参数信息,并通过仿真和实测数据验证了所提方法的有效性,理论和实验结果表明该方法只需要4个采样点就能实现对LFM信号的参数估计,并且实验中的参数估计误差均在3%以内,极大的提高有限新息率采样的参数估计效率。

转发式干扰条件下LFM雷达的检测概率估计

对多雷达干扰效果评估的难点在于分析干扰机对非目标雷达的影响。针对干扰机转发一部线性调频(linear frequency modulation,LFM)雷达的信号无意干扰另一部LFM雷达时的检测概率估计问题,首先计算了被干扰雷达对干扰信号在空域、频域和时域上的接收增益;其次将干扰信号在判决单元中的统计特性建模为非中心卡方分布,并给出了检测概率和虚警概率的计算方法。仿真结果表明,在一部干扰机的无意干扰下,估计的检测概率可作为被干扰雷达检测概率的上限;为达到同样的干扰效果,转发非目标雷达的信号实施干扰,比转发目标雷达的信号进行干扰所需的干扰功率更少。

MSK-LFM一体化信号波形相关性分析与参数选择

以二进制数字信号最佳接收准则为依据,分析了MSK-LFM雷达通信一体化信号不同码元对应波形的相关性。利用fresnel函数得到了波形相关系数的表达式;通过数值仿真得到了相关系数随LFM信号的初始频率、调频率、脉冲内码元调制速率等参数的变化关系;构建MSK-LFM信号正交调制、解调仿真模型进行验证。研究表明,通过增大初始频率、调频率或减少调制速率可降低信号误码率;当初始频率远大于脉冲内码元调制速率时可认为不同码元波形正交。

Chirp-Rate Resolution of Fractional Fourier Transform in Multi-component LFM Signal

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.

Wigner-Hough transform based on slice's entropy and its application to multi-LFM signal detection

To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and its corresponding characteristics, derives the probability density functions of the LFM signal and Gaussian white noise within WHT based on entropy (WHTE), dimension under different assumptions and puts forward a WHT algorithm based on entropy of slice to improve the capacity of detecting the LFM signal. Entropy of the WHT domain slice is adopted to assess the information size of polar radius or angle slice, which is converted into the weight factor to weight every slice. Double-deck weight is used to weaken the influences of noise and disturbance terms and WHTE treatment and signal detection procedure are also summarized. The rationality of the algorithm is demonstrated through theoretical analysis and formula derivation, the efficiency of the algorithm is verified by simulation comparison between WHT, fractional Fourier transform and periodic WHT, and it is highlighted that the WHTE algorithm has better detection accuracy and range of application against strong noise background.

Combining Radon-ambiguity transform with second-order difference to improve detection probability of LFM signals in low SNR

The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.

ALGORITHM FOR THE DETECTION AND PARAMETER ESTIMATION OF MULTICOMPONENT LFM SIGNALS

A novel algorithm based on Radon-Ambiguity Transform (RAT) and Adaptive Signal Decomposition (ASD) is presented for the detection and parameter estimation of multicompo-nent Linear Frequency Modulated (LFM) signals. The key problem lies in the chirplet estimation. Genetic algorithm is employed to search for the optimization parameter of chirplet. High estimation accuracy can be obtained even at low Signal-to-Noisc Ratio(SNR). Finally simulation results are provided to demonstrate the performance of the proposed algorithm.

Statistical performance of IF estimation of LFM signals with timevarying amplitude using the peak of WVD

The instantaneous frequency （IF） estimation of the linear frequency modulated （LFM） signals with time-varying amplitude using the peak of the Wigner-Ville distribution （WVD） is studied. Theoretical analysis shows that the estimation on LFM signals with time-varying amplitude is unbiased, only if WVD of time-varying amplitude reaches its maximum at frequency zero no matter in which time. The statistical performance in the case of additive white Guassian noise is evaluated and an analytical expression for the variance is provided. The simulations using LFM signals with Gaussian envelope testify that IF can be estimated accurately using the peak of WVD for four models of amplitude variation. Furthermore the statistical result of estimation on the signals with amplitude descending before rising is better than that of the signals with constant amplitude when the amplitude variation rate is moderate.

HIGH RESOLUTION RANGE PROFILE FORMATION BASED ON LFM SIGNAL FUSION OF MULTIPLE RADARS

This paper presents a new method of High Resolution Range (HRR) profile formation based on Linear Frequency Modulation (LFM) signal fusion of multiple radars with multiple frequency bands. The principle of the multiple radars signal fusion improving the range resolution is analyzed. With the analysis of return signals received by two radars,it is derived that the phase difference between the echoes varies almost linearly with respect to the frequency if the distance between two radars is neg-ligible compared with the radar observation distance. To compensate the phase difference,an en-tropy-minimization principle based compensation algorithm is proposed. During the fusion process,the B-splines interpolation method is applied to resample the signals for Fourier transform imaging. The theoretical analysis and simulations results show the proposed method can effectively increase signal bandwidth and provide a high resolution range profile.

Lorentz force electrical impedance tomography using pulse compression technique

Lorentz force electrical impedance tomography （LFEIT） combines ultrasound stimulation and electromagnetic field detection with the goal of creating a high contrast and high resolution hybrid imaging modality. In this study, pulse compression working together with a linearly frequency modulated ultrasound pulse was investigated in LFEIT. Experiments were done on agar phantoms having the same level of electrical conductivity as soft biological tissues. The results showed that：（i） LFEIT using pulse compression could detect the location of the electrical conductivity variations precisely; （ii） LFEIT using pulse compression could get the same performance of detecting electrical conductivity variations as the traditional LFEIT using high voltage narrow pulse but reduce the peak stimulating power to the transducer by 25.5 dB; （iii） axial resolution of 1 mm could be obtained using modulation frequency bandwidth 2 MHz.

Generalized Parseval’s Theorem on Fractional Fourier Transform for Discrete Signals and Filtering of LFM Signals

This paper investigates the generalized Parseval’s theorem of fractional Fourier transform (FRFT) for concentrated data. Also, in the framework of multiple FRFT domains, Parseval’s theorem reduces to an inequality with lower and upper bounds associated with FRFT parameters, named as generalized Parseval’s theorem by us. These results theoretically provide potential valuable applications in filtering, and examples of filtering for LFM signals in FRFT domains are demonstrated to support the derived conclusions.

Analysis and Improvement of the Real-Time Segmented Pulse Compression-Detection Algorithm

Real-Time segmented pulse compression-detection is one of the key technologies of space-borne tracking receiver. Its implementation requires an optimized and dedicated hardware. The real-time processing places several constraints such as area occupied, power comumption, and speed. A number of segmented compression techniques have been proposed to overcome these limitations and decrease the processing latency. However, relatively high power loss in the partial field could limit their implementation in many current real-time systems. A good theoretical model was designed with intersection signal accumulation to enhance signal- noise-ratio （SNR） gain of detecting signal in the paper. From the experimental results it is known that this approach works well for pulse compression-detection, which is better suited for implementation in the high performance of current field programmable gate array （FPGA） with dedicated hardware multipliers.

一种LFM雷达间歇非均匀采样噪声调制转发干扰方法

针对间歇采样转发干扰生成的假目标分布呈现较强规律性的问题,在间歇采样转发干扰方法基础上,结合非均匀采样与噪声调制的方法,给出了一种基于噪声乘积调制的间歇非均匀采样转发的干扰方法。通过对目标雷达信号进行非均匀采样与噪声乘积调制,在距离-速度维度内产生压制性干扰效果。仿真实验结果表明,该方法能够克服传统间歇采样直接转发干扰的假目标分布规律的问题,增大了干扰的作用范围。

基于相位重构的LFM信号间歇采样干扰产生方法研究

目前,对线性调频信号采用间歇采样干扰样式是电子自卫干扰的常用方法。由于收发延迟,干扰主峰落后于目标回波,但间歇采样可以获取超前于主峰信号的次峰目标。在线性调频斜率较小时,次峰目标甚至可以超前于被保护目标,但线性调频斜率较大时,次峰距离主峰近,效果难以得到保证。提出一种新方法,该方法基于相位信息通过对相位的线性拟合重构信号实现了信号的近似复原,使得主峰相对于回波的延迟被消除,且保持了良好的相参特性。