High resolution radar signal detection based on feature analysis

Transcription

1 Available online Journal of Chemical and Pharmaceutical Research, 4, 6(6):73-77 Research Article ISSN : CODEN(USA) : JCPRC5 High resolution radar signal detection based on feature analysis Xiaowei Niu and Zhiming He, School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu city, Sichuan, China School of Electronic and information engineering Chongqing Three Gorges University, Wan Zhou, China ABSTRACT The wideband radar signal has random arameters features, and traditional radar signal detection methods mainly detect the low resolution narrowband radar signal, the wideband and high resolution radar signal detection erformance is bad. An imroved high resolution wideband radar signal detection method is roosed based on feature analysis. A grou of full range of wideband high resolution radar signal features is extracted for analyzing the wideband high resolution features of radar signal accurately, the concet of level feature quantity accumulation oint is roosed, the scale factor and level factor can control the signal feature quantity, the resolution and the sensitivity of the radar signal are imroved, feature cluster analysis method is used in analyzing the radar signal, the feature relationshi of high resolution radar signal is analyzed, the artificial neural network algorithm is used to realize the detection of radar signal. Exeriment results show that the new method can imrove the radar signal detection efficiency and accuracy. Key words: feature; wideband high resolution radar signal; detection analysis INTRODUCTION With the raid develoment of science technology, the traditional narrow-band radar cannot adat to the current military requirements, the wideband radar with high range resolution has higher alication value. The wideband radar signal has better target range resolution, so it can classify and recognize the targets. It has good strong anti-interference caability, and it has good clutter suression erformance for the low altitude targets. Therefore, the wideband high resolution radar signal detection should be researched to imrove the detection erformance. The wideband high resolution radar signal has random arameters features, but traditional radar signal detection methods mainly detect the low resolution narrowband radar signal, the wideband and high resolution radar signal detection erformance is bad[]. In this aer, an imroved high resolution wideband radar signal detection method is roosed based on feature analysis. A grou of full range of wideband high resolution radar signal features is extracted for analyzing the wideband high resolution features of radar signal accurately, the concet of level feature quantity accumulation oint is roosed[], the scale factor and level factor can control the signal feature quantity, the resolution and the sensitivity of the radar signal are imroved, feature cluster analysis method is used in analyzing the radar signal, the feature relationshi of high resolution radar signal is analyzed, the artificial neural network algorithm is used to realize the detection of radar signal. Exeriment results show that the new method can imrove the radar signal detection efficiency and accuracy.. HIGH RESOLUTION RADAR SIGNAL DETECTION METHOD BASED ON FEATURE ANALYSIS.. Feature analysis of wideband high resolution radar signal In the recognition of the target distance, the clutter interference is serious, the amlitude of radar signal decreased. 73

2 Xiaowei Niu and Zhiming He J. Chem. Pharm. Res., 4, 6(6):73-77 With the increase of target distance, the wideband radar signal has been extended, the signal changes from single eak to dual eaks. When changing the object distance in the detection rocess, the length and width of wideband high resolution radar signal changes, the distance between signal two eak valley is stable, it shows that the effect of the linear relationshi is not affected by the signal resolution and wave length. The feature is effective[3]. In order to describe the width and deth of wideband high resolution radar signal, the above factors should be considered, through reeated exeriments, the following 3 features are extracted [4]. () Length of the radar signal Because the length of signal has interference to the amlitude of radar signal, so it can be used as a feature. Firstly, the otimal sensors regression radar signal length is l. m fl x (min z ) x (min z ) xn x m b b x n of radar signals should be solved, the distance of two eak valleys is fl, and the linear b mb xnb Where, a and b reresent the coefficients., l a fl + b () () Amlitude, it is the biggest difference between eak and valley of radar signal. n m m zmax max max { zxy} min{ zxy} y n x x () Radar signal deth affects the signal amlitude directly, it is the deth feature, and it is related to the length and width of the radar signal. (3) Feature of radar signal: E n m x n y z xy (3) The feature of radar signal E can reflect the three-dimensional size of radar signal comrehensively.. High resolution radar signal feature clustering analysis In order to obtain the recise analysis of the characteristics of broadband high resolution radar signal, the concets of λ horizontal characteristic quantity accumulation is introduced, and it can describe the characteristics of radar signal with resolution and sensitivity, the feature model of radar signal is created [5]. Assumed the wideband high resolution radar signal is x (t), windowing oeration is oerated on the signal, and the local feature variable feature is obtained. x (t) is samled, and the discrete signal x(n) is obtained, the width of rectangular window function h (t) is T ( d + ) Ts, Fs Ts is used to describe the samling frequency of radar signal, through the discrete oeration, it can obtain h( n),( n d,...,,,..., d). The ower x ( n) of x( n) h( n ni ) is the d scale ower E ( n d i, ) of radar signal x(n) at oint d + ni + d ni d n T i s.according to the setting ste, the osition of oint n T i s axis, the radar signal features are searched fully in the domain. For a given wideband high resolution radar signal (n) be reresented by E( n,d) resectively, for real value [,] then, i is adjusted, it makes the d scale ower slide on the x, the scale is d, assumed all d scale ower of (n) x can in average, the maximum value is max{ E ( n d i, )}, they are shown as E and µ,if ( f ( µ )) E + f ( µ ) E, ( f ( µ )) E + µ E. And λ su{ u E( n ( ) E } i µ + µ E f ( ). E It shows that the oint n is a λ level feature clustering oint of radar signal x (n ) in scale d, (µ ) T i s f is the 74

3 Xiaowei Niu and Zhiming He J. Chem. Pharm. Res., 4, 6(6):73-77 variable µ,it is from [,] to[,], it is a monotonically increasing function. The function f (µ) can modify the level signal λ, the aggregation degree of signal characteristic is imroved, oint E, at the same time, E( n i is large and close to the level n T i s is a level feature λ, value, in the range of radar signal artial characteristic quantity, it can ensure that the set oint, d scale feature clustering oint can E, the radar signal x(n) is a to level features, then λ reflect the quantity accumulation qualification, the λ value is higher, the oint features more gathered around. According to the radar signal feature, the radar signal feature oint shae model is constructed, and the oerational radar signals are clustered in the high feature aggregation area, the wideband high resolution radar signal can extract the characteristic frequency band of signal, the rocess analysis of radar signal quantity accumulation and feature extraction can be exressed as follows: () Comute the sectrum (ω) of radar signal x (n). () Select the scale d, calculate the d scale ower average value E of ower sectrum radar signal, the maximum value is E, the average value is E. (3) In accordance with the requirements, the horizontal feature feature clustering oint of radar signal (ω) is calculated. λ of λ is selected, and the λ horizontal (4) According to horizontal feature of λ, the feature model of radar signal is established in the frequency domain. As above analysis rocess, the wideband high resolution features of radar signal are extracted, and the concet of level characteristic quantity accumulation is roosed, the scale factor and factor can control the signal characteristic quantity, it can imrove the sensitivity and resolution of radar signal. According to the feature clustering radar signal feature analysis method, the feature relationshi of high resolution radar signal is analyzed, and the artificial neural network algorithm is used to realize the detection of radar signal..3 Artificial neural network algorithm and realization of detection algorithm Fig. Schematic diagram of the neural network Neural network detection model takes three layers of BP neural network to realize the nonlinear maing function of radar signal, it is shown in Figure, which is comosed of inut layer, hidden layer, outut layer, each layer of the neural network realizes the connection of different layers. The inut / outut samle way is used to obtain the backward roagation learning algorithm. If the outut layer obtain the exected outut result, ending. Conversely, reverse roagation is carried out. By connecting the reverse oeration error signal, the gradient descent method is used to modify each layer neuron weights and threshold, the error of radar signal is reduced. The algorithm rocess is exressed as follows: W () Assume that the initial weight () is the less random non-zero value. () Given inut / outut signal samles, and thus the network outut is obtained, the radar signal detection results are obtained. Assuming that the inut / outut results of th samle are: u ( u, u, L, un ) d ( d, d, L, dn ),,, L, L, (4) 75

4 Xiaowei Niu and Zhiming He J. Chem. Pharm. Res., 4, 6(6):73-77 When the P samle inut, the outut of node i is: y ( t) f [ x ( t)] f [ w ( t) I ] i i ij j j Where, I is used to describe the grou inut, and jth outut of node i is obtained, the function f (x) j S tye function as the objective function, it is: f ( x) x + e (6) (5) get the Through the hidden layer and outut layer, the radar detection result is obtained, and the outut of the network outut layer nodes is otimized. (3) Calculation of objective function J. Assume that E is used to reresent the objective function of samle, L is the norm, then: k k k k k E ( t) d y ( t) [ d y ( t)] e ( t) Wherein, (t) (7) y k is the Pth samle in the inut layer, after t weights adjustment, the network outut is obtained, and the objective function of the total network is: J ( t) E ( t) (8).4 Exeriment and result analysis In order to verify the validity of this method, we need the related exeriments analysis, a stealth lane is selected as the target, the radar incident wave is horizontal olarization, and the radial radar signal resolution is cm, the length of the target is.m. The wideband high resolution radar signal detection is taken with new method and traditional method, the wideband high resolution radar signal detection efficiency is shown in Figure. Fig Signal detection erformance From figure, we can conclude that the detection efficiency of new method is better than the traditional method, the detection robability reach to 99%, and it has higher erformance of radar signal detection. The detection erformance results are exressed in Table. It shows that the new method is better than the traditional method, and it has good alication value in ractice. Table Detection results comarison Method Detection seed Average error rate /% Average detection rate /% Average miss rate /% Proosed method Fast Traditional method Slow CONCLUSION In this aer, an imroved high resolution wideband radar signal detection method is roosed based on feature analysis. A grou of full range of wideband high resolution radar signal features is extracted for analyzing the wideband high resolution features of radar signal accurately, the concet of level feature quantity accumulation oint 76

5 Xiaowei Niu and Zhiming He J. Chem. Pharm. Res., 4, 6(6):73-77 is roosed, the scale factor and level factor can control the signal feature quantity, the resolution and the sensitivity of the radar signal are imroved, feature cluster analysis method is used in analyzing the radar signal, the feature relationshi of high resolution radar signal is analyzed, the artificial neural network algorithm is used to realize the detection of radar signal. Exeriment results show that the new method can imrove the radar signal detection efficiency and accuracy. Acknowledgments The authors wish to thank the National Natural Science Foundation of China for contract 649, the foundation Research Funds for the Central Universities (ZYGXJ3) and Oening Toic Fund for Key Laboratory of Comuter Architecture(CARCH3). And this work was also suorted by Technology Project Foundation of Chongqing Education Committee(KJ3),and Key Laboratory of signal and information rocessing Chongqing Three Gorges University, under which the resent work was ossible. REFERENCES [] Liu Xiangdong. Bulletin of Science and Technology, 3(): [] GAO Zhichun, CHEN Guanwei, HU Guangbo, et al. Comuter & Digital Engineering, 4(): [3] GUO Xiao-yan. Comuter Simulation, 3(3):8-. 4 [4] ZHENG Zhen, WANG Liyuan, ZHOU Yong. Chaos Shi Electronic Engineering, 33(5): [5] ZHANG Yan, REN An-hu. Science Technology and Engineering,; ():