In this paper,based on the feature of high resolution one-dimensional range profile,two effective motion compensation methods are presented. Firstly,the processing method of stepped-frequency and the response of target moving to range profile are analyzed. Secondly,the function of range profile entropy and range profile contrast are presented for velocity compensation,and then the theory analysis,math model,and solution method are analyzed in detail. Finally,several simulation experiments are designed to prove the accuracy and effectiveness of these two methods. From the final theory analysis and simulation experiments,the conclusion can be drawn that these two methods are effective,which can get much higher velocity estimation accuracy,well real-time and easy to be used in project application. After motion compens-ation,the high resolution one-dimensional range profile will be much better than that used to be,and is used for the detection, recognition and ranging of moving targets.
Traditional Sobel algorithm is deeply influenced by Gaussian noise,therefore,before boundary extraction,mean filter should be done. But the filtering process is always over-smooth images'details of certain directions,so that images'edges will not be extracted correctly. Aiming at this problem,this paper puts forward a detection algorithm based on edge-preserving characteristics,by matching edge mould of different directions to definite edge preserving directions. Instead of the mean filter process,this algorithm improves the performance of traditional algorithms,and provides the simulation results. The experiment results prove that this algorithm preserves more images'edge information when canceling noise.
The current parameter estimation algorithms of chirp rate have high complexity and long calculation time,meantime they are difficult to achieve high estimation rate. Therefore,in order to overcome these problems,in this paper,a new parameter estimation algorithm based on Holder coefficient is presented. Firstly,this algorithm calculates the correlation curve of the Holder coefficient value under different chirp rate. Secondly,this algorithm calculates the correlation curve under different SNR. Finally,the fitting curve expression can be got by the correlation curve,and then the estimation value of chirp rate can also be got. The theory analysis and simulation results show that this algorithm is simple and easy to realize,and has much better application value for real-time estimation.
In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.
In the fusion of image,how to measure the local character and clarity is called activity measurement. According to the problem,the traditional measurement is decided only by the high-frequency detail coefficients, which will make the energy expression insufficient to reflect the local clarity. Therefore,in this paper,a novel construction method for activity measurement is proposed. Firstly,it uses the wavelet decomposition for the fusion resource image, and then utilizes the high and low frequency wavelet coefficients synthetically. Meantime,it takes the normalized variance as the weight of high-frequency energy. Secondly,it calculates the measurement by the weighted energy,which can be used to measure the local character. Finally,the fusion coefficients can be got. In order to illustrate the superiority of this new method,three kinds of assessing indicators are provided. The experiment results show that,comparing with the traditional methods,this new method weakens the fuzzy and promotes the indicator value. Therefore,it has much more advantages for practical application.
In this paper,convex optimization theory is introduced into the recognition of communication signals. The detailed content contains three parts. The first part gives a survey of basic concepts,main technology and recognition model of convex optimization theory. Special emphasis is placed on how to set up the new recognition model of communication signals with multisensor reports. The second part gives the solution method of the recognition model,which is called Logarithmic Penalty Barrier Function. The last part gives several numeric simulations,in contrast to D-S evidence inference method,this new method can also generate reasonable recognition results. Moreover,this new method can deal with the form of sensor reports which is more general than that allowed by the D-S evidence inference method,and it has much lower computation complexity than that of D-S evidence inference method. In addition,this new method has better recognition result,stronger anti-interference and robustness. Therefore,the convex optimization methods can be widely used in the recognition of communication signals.
Jin-Feng PangYun LinXiao-Chun XuZheng DouZi-Cheng Wang
Based on the advantage of phase coded signal and stepped frequency signal,a new hybrid modulation signal is introduced in this paper. It combines phase code modulation during the pulse with stepped frequency modulation between the pulses, which is named as phase-coded stepped-frequency ( PCSF ) signal. By analyzing its waveform and ambiguity function,the comparison between Stepped-Frequency ( SF) signal and PCSF signal is given,which shows that the PCSF signal is better than SF signal. Finally,the signal processing method with two stage compressed processing is presented. The simulation results show that this new hybrid modulation radar signal can get a higher stepped frequency than ordinary SF signal,realize the same equivalent bandwidth with less pulse number,and solve the conflict among the stepped frequency,the number of pulse, and transmit average power. Under the premises of a certain range resolution,this new hybrid modulation radar signal not only raises the data rate of radar system,but also reduces Doppler sensitivity with a good prospect, and the effect of one-dimensional range profile is much better than that of traditional SF signal. Therefore,this new hybrid modulation radar signal can be widely used in application.
