Research On The Method Of Linearly Modulated Signal Analysis Based On The Detection And Estimation Of Sinusoidal Wave

An important technology called communication signal modulation analysis(CSMA)will be used if the third party in non-cooperative communication wants to surveil the activity of communication or even decipher its content for some special purpose.Although with little prior knowledge,CSMA can provide the estimation of some key parameters,such as carrier frequency and symbol rate,and determine the modulation types ultimately.As much as we know,CSMA can be found in many applications including Radio Reconnaissance,Non-Communication Intelligence Reconnaissance,Electronic Warfare,Radio Spectrum Management,and Software-Defined Radio.CSMA is highly related to signal demodulation because of the same object and many common tasks.As a result,some algorithm found in signal demodulation can also be used for reference by CSMA.However,CSMA is much more challenging than demodulation because of a good many disadvantageous factor.CSMA can be divided into the estimation of unknown paramters and the classification of modulation types.From the point of view of pattern recogonition,modulation classification is also composed of classifying feature extraction,samples feature set construction and classifying algorithm design,and parameter estimation will only be assistant.From the point of view of statistical signal processing,parameter estimation and modulation classification,which can be performed through signal detection,are equally interrelated.This paper discusses the parameters estimation and modulation classification of linearly modulated signals on the theory of sinusoidal signal detection and estimation,a basic signal processing method can be found in all kinds of applications.The modulated signal set is composed of BPSK,QPSK,8PSK,OQPSK(MSK,Ï€/2 BPSK),Ï€/4 QPSK,16QAM,32QAM, 64QAM,128QAM,256QAM.This paper gives out a new definition called local SNR to describe the quality of sinusoidal wave in colored noise.Local SNR is the ratio of the signal power to the variance of a nominal white noise,whose power spectrum density equals that of colored noise where the spectral line of sinusoidal wave is located.Based on a general model of linearly modulated signals,this paper also discusses how to calculate E_sN₀,which equals the ratio of energy per symbol to power spectrum density of noise.A series of computer simulations indicate that the background noise of CSMA is colored and non-Gaussian,which leads to the difficulty in CSMA.A new definition called signal MAC(Moving Averaging and Comparing)spectrum, which can be got by calculating the ratio of every frequency bin and its nearby ones of magnitude spectrum and is immune from the magnitude spectrum fluctuation of colored noise, has been proposed for sinusoidal wave detecting and estimating in colored noise.Combining corresponding nonlinear transform and signal MAC spectrum,two signal classifying algorithm have been given.The one is 2^k-Power algorithm for classification of BPSK/QPSK/8PSK,the other is C-DOT(Classifier on Detecting Offset-Timing)algorithm for classification of offset modulated signal(MSK and OQPSK,for example)and non-offset modulated signal(QPSK and QAM,for example).Based on digitally heterodyning,filtering and decimating,this paper puts forward the FFT-Kay algorithm,which owns good estimation precision and low noise threshold,for frequency estimation of sinusoidal wave in white noise.It is important that the FFT-Kay algorithm is comparable to the theoretic optimum MLE(Maximum-Likelihood Estimator) algorithm.Combined with signal MAC spectrum,the FFT-Kay algorithm can be easily extended to MAC-Kay algorithm,which can be used for frequency estimation of sinusoidal wave in colored noise.Following different nonlinear transform,above-mentioned two algorithms can be used to estimate the carrier frequency and symbol rate with high precision.There are many accidents in CSMA because of its highly complicated application background.Two algorithms for countermeasure have been given to illustrate how these accidents can be dealt;the detection of periodic sequence and invalid channel equalization.Such algorithms are strongly recommended if wrong conclusion is unexpected in CSMA.The application of above-mentioned algorithms indicates that the theory of sinusoidal wave detection and estimation can resolve many technique issues appearing in CSMA.