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.

Gauss linear frequency modulation wavelet transforms and its application to seismic phases identification

Based on the characteristics of gradual change style seismic signal onset which has more high frequency signal components but less magnitude, this paper selects Gauss linear frequency modulation wavelet as base function to study the change characteristics of Gauss linear frequency modulation wavelet transform with difference wavelet and signal parameters, analyzes the error origin of seismic phases identification on the basis of Gauss linear frequency modulation wavelet transform, puts forward a kind of new method identifying gradual change style seismic phases with background noise which is called fixed scale wavelet transform ratio, and presents application examples about simulation digital signal and actual seismic phases recording onsets identification.

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).

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.

A Novel Orthogonal LoRa Multiple Access Algorithm for Satellite Internet of Things

In recent years,LoRa has been extensively researched in the satellite Internet of Things(IoT).However,the multiple access technology of LoRa is still one of the bottlenecks of satellite IoT.To improve the multiple access performance of LoRa satellite IoT,based on the orthogonality of LoRa symbols in the fractional domain,this paper proposes a low complexity Orthogonal LoRa Multiple Access(OLMA)algorithm for multiple LoRa users occupying the same frequency bandwidth.The algorithm introduces the address code to divide the fractional bandwidth into multiple parts,and the OLMA users with different address codes occupy different parts to transmit the information code,thus avoiding mutual interference caused by collisions in the same frequency bandwidth.The multiple access capability of OLMA can be flexibly configured only by simply adjusting the length of the address code according to the actual application requirements of data transmission.Theoretical analysis and simulation results show that the OLMA algorithm can greatly improve the multiple access capability and the total transmission bit rate of LoRa IoT without changing the existing LoRa modulation parameters and process.

Novel LFM Jammer Suppression Algorithm for DSSS in FRFT Domain

A novel algorithm is proposed to resolve the defects in the traditional linear frequency modulation(LFM)jamming suppression algorithm in the fractional Fourier transform(FRFT)domain.The traditional LFM jamming suppression algorithm in the FRFT domain has some defects.For example,the exact threshold is difficult to set and both the signal-to-noise ratio(SNR)loss and spectrum leakage are serious in strong jamming-to-signal ratio(JSR)situations.Windowing,overlapping and inverse windowing techniques are used in the FRFT domain to reduce the spectrum leakage and the SNR loss.Under the condition that only the direct sequence spread spectrum(DSSS)signal and white Gaussian noise are present,the amplitude of the received signal after FRFT is assumed to be Rayleigh distributed.Based on the distribution characteristic,hypothesis testing is used to suppress the jamming spectrum using the algorithm.Simulation results show that the performance of proposed algorithm is better than that of the conventional algorithms,especially in a strong jamming and multi component LFM jamming environment.

A high performance waveform and a new ranging method for the proximity detector

Signal modulation is an essential design factor for proximity detectors and directly affects the system's potential performance.In order to achieve the advantages of chaotic codes bi-phase modulation(CCBPM)and linear frequency modulation(LFM) simultaneously,this paper designed a waveform which combined chaotic codes bi-phase modulation and linear frequency modulation(CCBPM-LFM) for proximity detectors.The CCBPM-LFM waveform was analyzed in the aspect of time delay resolution(TDR) and Doppler tolerance(DT) based on ambiguity function(AF).Then,a ranging method,which we called instant correlation harmonic demodulation(ICHD),was presented for the detector using the CCBPM-LFM waveform.By combining time domain instant correlation with harmonic demodulation,the ICHD solved the problem caused by combination modulation and made the most of the linear frequency modulation(LFM) harmonics and the correlation of chaotic codes.Finally,a prototype was implemented and ranging experiments were carried out.From the theoretical analysis and experimental results,the proximity detector used the CCBPM-LFM waveform has an outstanding detection performance.

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 consumption,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 signalnoise-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.

Multi-component LFM signal detection and parameter estimation based on Radon-HHT

A new method is proposed to analyze multi-component linear frequency modulated （LFM） signals, which eliminates cross terms in conventional Wigner-Ville distribution （WVD）. The approach is based on Radon transform and Hilbert-Huang transform （HHT）, which is a recently developed method adaptive to non-linear and non-stationary signals. The complicated signal is decomposed into several intrinsic mode functions （IMF） by the empirical mode decomposition （EMD）, which makes the consequent instantaneous frequency meaningful. After the instantaneous frequency and Hilbert spectrum are computed, multi-component LFM signals detection and parameter estimation are obtained using Radon transform on the Hilbert spectrum plane. The simulation results show its feasibility and effectiveness.

Mathematic principle of active jamming against wideband LFM radar

The inherent mathematic principle of active jamming against the wideband linear frequency modulated（LFM） radar is investigated. According to different generation strategies, the active jamming methods are reclassified into three groups, i.e.,non-coherent jamming（NCJ）, convolution jamming（CJ） and multiplying jamming（MJ）. Based on the classification, the mathematic principles of different active jamming groups are put forward, which describe the relationships between the modulated signals and the jamming results. The advantages and disadvantages of different groups are further analyzed, which provides a new perspective for the study of jamming/anti-jamming methods and a potential for engineers to integrate similar jamming methods into one jammer platform. The analyses and simulation results of some typical active jamming methods prove the validity of the proposed mathematics principle.

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.

Adaptive digital self-interference cancellation based on fractional order LMS in LFMCW radar

Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.

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.

Speed-Direction Sensing under Multiple Vehicles Scenario Using Photonic Radars

Recent reports from World Health Organization(WHO)show the impact of human negligence as a serious concern for road accidents and casualties worldwide.There are number of reasons which led to this negligence;hence,need of intelligent transportation system(ITS)gains more attention from researchers worldwide.For achieving such autonomy different sensors are involved in autonomous vehicles which can sense road conditions and warn the control system about possible hazards.This work is focused on designing one such sensor system which can detect and range multiple targets under the impact of adverse atmospheric conditions.A high-speed Linear Frequency Modulated Continuous Wave(LFMCW)based Photonic Radar is proposed to detect multiple targets by integrating Mode division multiplexing(MDM).Reported results in terms of range frequency,Doppler frequency and range resolution are demonstrated using numerical simulations with the bandwidths of 1 and 4 GHz and under adverse atmospheric conditions carrying 75 dB/km of attenuation.To prove the effectiveness of the proposed photonic radar,moving targets are also demonstrated with different speed.System reported substantial range resolution of 15 cm using 1 GHz of bandwidth and 3 cm using 4 GHz of bandwidth.

Frequency-modulated continuous-wave dual-frequency LIDAR based on a monolithic integrated two-section DFB laser

We demonstrate a high-resolution frequency-modulated continuous-wave dual-frequency LIDAR system based on a monolithic integrated two-section(TS) distributed feedback(DFB) laser. In order to achieve phase locking of the two lasers in the TS-DFB laser, the sideband optical injection locking technique is employed. A high-quality linear frequency-modulated signal is achieved from the TS-DFB laser. Utilizing the proposed LIDAR system, the distance and velocity of a target can be measured accurately. The maximum relative errors of distance and velocity measurement are 1.6% and 3.18%, respectively.

WHT-Based Detection and Parameter Estimation of a Single LFM Interference Signal in Spread Spectrum Systems

A method is presented for the detection and parameter estimation of a single Linear Frequency Modulation (LFM) signal in spread spectrum systems based on Wigner Hough Transform (WHT) , followed by the theoretical analysis. A simulation result is given to show the effectiveness of this method.

Concurrent photonic measurement of angle-of-arrival and chirp rate of microwave LFM signal

A photonic approach to concurrently measure the angle-of-arrival(AOA) and the chirp rate of a linear frequency modulated(LFM) signal is proposed and experimentally demonstrated. The measurement is achieved by estimating the differential frequency of a two-tone signal output by a dual-parallel Mach–Zehnder modulator and an additional asymmetry Mach–Zehnder interferometer. Experiments show that the AOA and the chirp rate are measured simultaneously, with an AOA measurement error of ?0.1° at an signal-to-noise ratio(SNR) of 9.6 d B.When the SNR is-10.4 d B, the AOA error is ?1.3°, and the chirp rate, measured as 210.2 ? 1.5 Hz∕ps, has a standard deviation of 0.7%. The measured chirp rate agrees well with the real LFM signal.

An approach for parameter estimation of combined CPPM and LFM radar signal

In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval （PRI） of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform （CHT） algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio （SNR） is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.

Researches in microwave photonics based packages for millimeter wave system with wide bandwidth and large dynamic range

This paper presents an introduction to the researches in microwave photonics based packages and its application, a 973 project （No. 2012CB315600）, which focuses on addressing new requirements for millimeter wave （MMW） system to work with higher frequency, wider bandwidth, larger dynamic range and longer distance of signal distribution. Its key scientific problems, main research contents and objectives are briefed, and some latest achievements by the project team, including generation of linear frequency modulation wave （LFMW）, tunable optoelectronic oscillator （OEO） with lower phase noise, reconfigurable filter with higher Q value, time delay line with wider frequency range, down conversion with gain, and local oscillator （LO） transmission with stable phase, are introduced briefly.