Periodic signal extraction of GNSS height time series based on adaptive singular spectrum analysis

Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.

Microwave and IF Cancellation of Leakage Signal for Spread Spectrum Radar

This paper discusses the requirements for the cancellation of leakage signal, analyzes in detail the principals of cancelling leakage signal in microwave and IF band, and proposes the schemes to realize adaptive cancellation. Computer analog has shown that the proposed scheme has a very high convergence speed and can reach a high cancellation ratio.

Radar-Communication Integration Based on MSK-LFM Spread Spectrum Signal

At present, with the progress and innovation of technology, the radar communication dual function wave has become a hot research at home and abroad. Excellent integrated waveform can make full use resources of combat platform, reduce the size of equipment, and realize the actual functionality of the reality of the battle-field without affecting the radar communication func-tion. The MSK-LFM dual-function wave is a typical representative;it is based on LFM, through the MSK modulation to achieve the integration function. This paper proposes a scheme of combining the spread spectrum technology with the MSK-LFM waveform based on the previous literature. The simulation results show that the waveform envelope is more stable and the energy is more concentrated. With the introduction of spread-spectrum technology, the new waveform ambiguity function graph is much closer to the thumbtack than the traditional MSK-LFM waveform.

A novel dense spectrum correction algorithm for extracting vibration signals in internal combustion engine and its application

The algorithm of dense spectrum correction has been raised and proved based on the correction of discrete spectrum by fast Fourier transform.The result of simulation shows that such algorithm has advantages of high accuracy and small amount of calculation.The algorithm has been successfully applied to the analysis of vibration signals from internal combustion engine.To calculate discrete spectrum,fast Fourier transform has been used to calculate the discrete spectrum by the signals acquired by the sensors on the oil pan,and the signal has been extracted from the mixed signals.

Measurements of ocean wave spectrum from airborne radar at small incidence angles

This paper proposes the retrieval method of ocean wave spectrum for airborne radar observations at small incidence angles, which is slightly modified from the method developed by Hauser. Firstly, it makes use of integration method to estimate total mean square slope instead of fitting method, which aims to reduce the affects of fluctuations superposed on normalized radar cross-section by integration. Secondly, for eliminating the noise spectrum contained in signal spectrum, the method considers the signal spectrum in certain look direction without any long wave components as the assumed noise spectrum, which would be subtracted from signal spectrum in any look direction for linear wave spectrum retrieval. Estimated v from the integration method are lower than the one from fitting method and have a standard deviation of 0.004 between them approximately. The assumed noise spectrum energy almost has no big variations along with the wave number and is slightly lower to the high wave number part of signal spectrum in any look direction, which follows that the assumption makes sense. The retrieved directional spectra are compared with the buoy records in terms of peak wavelength, peak direction and the significant wave height. Comparisons show that the retrieved peak wavelength and significant wave height are slightly higher than the buoy records but don＇t differs significantly （error less than 10%）. For peak direction, the swell waves in first case basically propagate in the wind direction 6 hours ago and the wind-generated waves in second case also propagate in the wind direction, but the 180° ambiguity remains. Results show that the modified method can carry out the retrieval of directional wave spectrum.

Modulation recognition of MIMO radar signal based on joint HOS and SNR algorithm

This paper presents a joint high order statistics （HOS） and signal-to-noise ratio （SNR） algorithm for the recognition of multiple-input multiple-output （MIMO） radar signal without a priori knowledge of the signal parameters. This method is capable of recognizing the MIMO radar signal as well as discriminating it from single-carrier signal adopted by conventional radar. Meanwhile, the sub-carrier number of the none-coding MIMO radar signal is estimated. Extensive simulations are carried out in different operating conditions. Simulation results prove the feasibility and indicate that the recognition probability could reach over 90% when the value of SNR is above 0 dB.

Estimation of sea clutter inherent Doppler spectrum from shipborne S-band radar sea echo

Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas.However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter,so the sea clutter inherent spectrum must be estimated prior to investigating the sea clutter Doppler characteristics from the shipborne radar sea echo.In this paper we show some results about a shipborne sea clutter measurement experiment that was conducted in the South China Sea in a period between 2017 and 2018;abundant clutter data have been collected by using a shipborne S-band clutter measurement radar.To obtain the sea clutter inherent Doppler spectrum from these data,an estimation method,based on the mapping relationship between the shipborne clutter spectrum and the inherent clutter spectrum,is proposed.This method is validated by shipborne clutter data sets under the same measuring conditions except for the ship speed.Using this method,the characteristics of the Doppler spectrum lineshapes in the South China Sea are calculated and analyzed according to different sea states,wave directions,and radar resolutions,which can be instrumental in designing the radar target detection algorithms.

EFFICIENT STRIP-MODE SAR RAW SIGNAL SIMULATION OF MIXED TARGETS BASED ON ACCURATE 2-D SPECTRUM

An accurate and efficient Synthetic Aperture Radar(SAR)raw data generator is of considerable value for testing system parameters and verifying imaging algorithms.Nevertheless,the existing simulator cannot exactly handle the case of the fast moving targets in high squint geometry.As for the issue,the analytical expression for the two Dimensional(2-D)signal spectrum of moving targets is derived and a fast raw echo simulation method is proposed in this study.The proposed simulator can accommodate the moving targets in the high squint geometry,whose processing steps of the simulation are given in detail and its computational complexity is analyzed.The simulation data for static and moving targets are processed and analyzed,and the results are given to validate the effectiveness of the proposed approach.

High-Sensitivity Acquisition of Ultrahigh Dynamic Direct Sequence Spread Spectrum Signals in Space Communications

According to the requirements of the high-sensitivity acquisition of Direct Sequence Spread Spectrum(DSSS) signals under ultrahigh dynamic environments in space communications, a three-dimensional joint search of the phase of Pseudo-Noise-code(PN-code),Doppler frequency and its rate-of-change is presented to achieve high sensitivity in sensing high-frequency dynamics. By eliminating the correlation peak loss caused by ultrahigh Doppler frequency and its rate-of-change offset,the proposed method improves the acquisition sensitivity by increasing the non-coherent accumulation time. The validity of the algorithm is proved by theoretical analysis and simulation results. It is shown that signals with a carrier- to-noise ratio as low as 39 dBHz can be captured with high performance when the Doppler frequency is up to ±1 MHz and its rate-of-change is up to ±200 kHz/s.

Kravchenko probabilityweight functions in problems of radar signals correlation processing

In this report the combined method of correlation radar signal(RS)processing based on the theory of atomic functions(AF)is examined.Examples of using of new Kravchenko probability weight functions(WF)designs are presented.Quality functional to estimate accuracy and efficiency of RS processing for concrete physical models is constructed.It is shown that the proposed approach significantly improves the quality of the coherent analysis of RS.

Design of a Radar Signal Simulator Based on Virtex-Ⅱ Series FPGA

A simulation method to simulate the pseudorandom code P. M PP radar＇ s echo signal is proposed that makes use of the pre-generated Doppler simulation data, according to the relative movement parameter of the radar and the target. It resolves the problem of the high precision distance simulation and the high speed digital shift phase. At the same time, the radar dynamic digital video frequency target signal simulator is designed. Simulation results of the critical unit and the output waveform are given. The result of the test satisfies the system＇s request.

Implementation of a kind of FPGA-based binary phase coded radar signal processor architecture

A flexible field programmable gate array based radar signal processor is presented. The radar signal processor mainly consists of five functional modules： radar system timer, binary phase coded pulse compression（PC）, moving target detection （MTD）, constant false alarm rate （CFAR） and target dots processing. Preliminary target dots information is obtained in PC, MTD, and CFAR modules and Nios I! CPU is used for target dots combination and false sidelobe target removing. Sys- tem on programmable chip （SOPC） technique is adopted in the system in which SDRAM is used to cache data. Finally, a FPGA-based binary phase coded radar signal processor is realized and simula- tion result is given.

Application of Wavelet Packet Energy Spectrum to Extract the Feature of the Pulse Signal

The wavelet packet is presented as a new kind of multiscale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper. A new application approach of the wavelet packed method to extract the feature of the pulse signal from energy distributing angle is expatiated. It is convenient for the microchip to process and judge by using the wavelet packet analysis method to make the pulse signals quantized and analyzed. Kinds of experiments are simulated in the lab, and the experiments prove that it is a convenient and accurate method to extract the feature of the pulse signal based on wavelet packed-energy spectrumanalysis.

Line Spectrum Enhancement of Underwater Acoustic Signals Using Kalman Filter

To detect weak underwater acoustic signals radiated by submarines and other underwater equipment,an effective line spectrum enhancement algorithm based on Kalman filter and FFT processing is proposed.The proposed algorithm first determines the frequency components of the weak underwater signal and then filters the signal to enhance the line spectrum,thereby improving the signal-to-noise ratio(SNR).This paper discussed two cases:one is a simulated signal consisting of a dual-frequency sinusoidal periodic signal and Gaussian white noise,and the signal is received after passing through a Rayleigh fading channel;the other is a ship signal recorded from the South China Sea.The results show that the line spectrum of the underwater acoustic signal could be effectively enhanced in both cases,and the filtered waveform is smoother.The analysis of simulated signals and ship signal reflects the effectiveness of the proposed algorithm.

IMMUNE RBF NETWORK AND ITS APPLICATION IN THE MODULATION-STYLE RECOGNITION OF RADAR SIGNALS

Based on Immune Programming(IP), a novel Radial Basis Function (RBF) networkdesigning method is proposed. Through extracting the preliminary knowledge about the widthof the basis function as the vaccine to form the immune operator, the algorithm reduces thesearching space of canonical algorithm and improves the convergence speed. The application ofthe RBF network trained with the algorithm in the modulation-style recognition of radar signalsdemonstrates that the network has a fast convergence speed with good performances.

Key Radar Signal Sorting and Recognition Method Based on Clustering Combined with PRI Transform Algorithm

In this paper,we investigate the problem of key radar signal sorting and recognition in electronic intelligence(ELINT).Our major contribution is the development of a combined approach based on clustering and pulse repetition interval(PRI)transform algorithm,to solve the problem that the traditional methods based on pulse description word(PDW)were not exclusively targeted at tiny particular signals and were less time-efficient.We achieve this in three steps:firstly,PDW presorting is carried out by the DBSCAN(Density-Based Spatial Clustering of Applications with Noise)clustering algorithm,and then PRI estimates of each cluster are obtained by the PRI transform algorithm.Finally,by judging the matching between various PRI estimates and key targets,it is determined whether the current signal contains key target signals or not.Simulation results show that the proposed method should improve the time efficiency of key signal recognition and deal with the complex signal environment with noise interference and overlapping signals.

SENSORING DROPLET SPRAY TRANSFER IN MIG WELDING BASED ON ARC SPECTRUM SIGNAL

The method to detect droplet transfer by means of arc spectrum, while the experiment sets, testing principle and data processing procedure,are presented. The experiment and analysis results show that arc spectrum signal can be utilized to detect and measure the transfer procedure, the transfer modes and the transfer parameters. The arc spectrum signal enjoys excellent quality with high signal amplitude. Each transfer mode has its specific typical signal mode, and the pulse outline corresponds to an integrated transferring procedure of one droplet. All these features of arc spectrum signal can be easily applied hi the control of transfer procedure,the identification and stabilization of transfer mode and the measurement of transfer parameters.

Parameterized time-frequency analysis to separate multi-radar signals

Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.

Non-Supervised Learning for Spread Spectrum Signal Pseudo-Noise Sequence Acquisition

An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a self-organizing feature map（SOFM） neural network algorithm to detect and identify the PN sequence. A non-supervised learning algorithm is proposed according the Kohonen rule in SOFM. The blind algorithm can also estimate the PN sequence in a low signal-to-noise（SNR） and computer simulation demonstrates that the algorithm is effective. Compared with the traditional correlation algorithm based on slip-correlation, the proposed algorithm＇s bit error rate（BER） and complexity are lower.

A reweighted damped singular spectrum analysis method for robust seismic noise suppression

(Multichannel)Singular spectrum analysis is considered as one of the most effective methods for seismic incoherent noise suppression.It utilizes the low-rank feature of seismic signal and regards the noise suppression as a low-rank reconstruction problem.However,in some cases the seismic geophones receive some erratic disturbances and the amplitudes are dramatically larger than other receivers.The presence of this kind of noise,called erratic noise,makes singular spectrum analysis(SSA)reconstruction unstable and has undesirable effects on the final results.We robustify the low-rank reconstruction of seismic data by a reweighted damped SSA(RD-SSA)method.It incorporates the damped SSA,an improved version of SSA,into a reweighted framework.The damping operator is used to weaken the artificial disturbance introduced by the low-rank projection of both erratic and random noise.The central idea of the RD-SSA method is to iteratively approximate the observed data with the quadratic norm for the first iteration and the Tukeys bisquare norm for the rest iterations.The RD-SSA method can suppress seismic incoherent noise and keep the reconstruction process robust to the erratic disturbance.The feasibility of RD-SSA is validated via both synthetic and field data examples.