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    • Richa Gupta, Onkar Chand / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.326-329 Analysing Chebyshev Filter For Displaying Radar Target Track Richa Gupta , Onkar ChandABSTRACT Now-a-days, noises are common in property that they minimize the error between thecommunication channels and the recovery of the idealized filter characteristics and the actual over thetransmitted signals from the communication path range of the filter, but with ripples in the passband.without any noise are considered as one of the This type of filter is named in honour ofdifficult tasks. This is accomplished by the Pafnuty Chebyshev because their mathematicaldenoising techniques that remove noises from a characteristics are derived from Chebyshevdigital signal. The noise in the radar data results Polynomials. Because of the passband ripple inherentin the flutter of the flight target in display screen, in Chebyshev filters, filters which have a smootherwhich may disturb observer. This paper involves response in the passband but a more irregularthe use of Chebyshev filter for removing the noise response in the stopband are preferred for somefrom radar signal so that we can receive the clear applications.picture of Radar Signal which is to be displayed. The gain (or amplitude) response as aChebyshev filters are analog or digital filters function of angular frequency ω of the n th order lowhaving steeper roll off and more passband ripple pass filter is:(type 1) and stopband ripple (type 2) thanButterworth filters. Chebyshev filters have the Gn (ω) = |Hn(jω)| = 1 (1)property that they minimize the error between the √1+ε2 Tn2 (ω/ω0)idealized filter characteristics and the actual overthe range of the filter, but with ripples in the Where ε is the ripple factor, w0 is the cutoffpassband. By passing the radar signal through the frequency and Tn is Chebyshev polynomial of the nthChebyshev filter noise in radar signal is order.magnified. The results of MATLAB illustration The passband exhibits equiripple behavior,show that the method has a reliable denoising with the ripple determined by the ripple factor ε. Inperformance. the passband, the Chebyshev polynomial alternates between 0 and 1 so the filter gain alternate betweenKEYWORDS: Radar target track, Chebyshev maxima at G =1 and minima at G = 1 / √1+ε2filter, Butterworth filter, Denoising, Passband, At the cutoff frequency w0 the gain again has someStopband. value but continues to drop into the stopband as the frequency increases. The order of a Chebyshev filterINTRODUCTION is equal to the number of reactive components needed A mass of noise signal is always involved in to realize the filter using analog electronics. Thethe radar target track data for the effects of radar ripple is often given in dB.clutter, cloud, rain, and radar cross-section (RCS) andso on. The noise disturbs the target identification in Ripple in dB = 20log10 1 / √1+ε2 (2)the display screen, which causes the illusion thetarget is fluttering. Many filter techniques to resolve An even steeper roll off can be obtained ifthis problem, such as Kalman filtering, least squares allowed for ripple in the stopband, by allowing zeroesprocedure, are state estimation methods based on on the jw axis in the complex plane. This willtime series, and must consider the target’s past state, however result in less suppression in the stopband.locus model, and interrelated prior knowledge. But, The result is called an elliptic filter, also known asfor the time-varying system, all that information is Cauer filter. The above expression yields the poles ofdifficult to acquire, or is inaccuracy [1][2][3], leading the gain G .For each complex pole there is anotherto a worse result for the data of detail section[4]. which is the complex conjugate and for eachThereby, with Chebyshev Filter, a method filtering conjugate pair there are two more that are theradar target track is proposed in this paper. In the negatives of the pair. The transfer function must beend, the MATLAB simulation shows the method stable, so that its poles will be those of the gain thatavailability. have negative real parts and therefore lie in the left half plane of complex frequency space. The transferCHEBYSHEV FILTER DESIGNING function is then given by: Chebyshev filters are analog or digital filtershaving steeper roll off and more passband ripple n(type 1) and stopband ripple (type 2) than H (s) = 1 Π 1Butterworth filters. Chebyshev filters have the 2n-1ε m=1 (s – spm) (3) 326 | P a g e
    • Richa Gupta, Onkar Chand / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.326-329There are only those poles with a negative sign in frequency response magnitude at wp or w1front of the real term in the above equation for the and w2.poles. 5. It converts the state-space filter back to transfer function or zero-pole-gain form, as required. FILTERING METHOD FOR RADAR TARGET TRACK Compared with the magnitude of radar data in space-time plane, the power of noise or error is very weak. For example, generally, the order of magnitude of radar data is 106 meter in geocentric coordinate system, but the error is only severalFigure1: Gain and Group Delay of hundred meter at most. So the data of error must beChebyshev Filter converted to increase the signal-to-noise ratio (SNR). As being analyzed in frequency-domain, the The group delay is defined as the derivative conversion does not deteriorate the result to acquireof the phase with respect to the angular frequency the information of error’s frequency. The conversionand is measure of the distortion in the signal uses the first point in the data as a reference to realizeintroduced by phase differences for different to extract the noise information. As shown in thefrequencies. Equation below: e (t) = x(t) / x(1) −1 (5) ζg = -d/dω arg(H(jω)) (4) Then e (t) is the one to be filtered, and the formula is: The gain and the group delay for a fifthorder type 1 Chebyshev filter with ε = 0.5 are plottedin the above graph.It can be seen that there are ripplesin the gain and the group delay in the passband butnot in the stopband.In this paper only type I filter isdesigned and used[5]. This method has followingadvantages: (a) the poles of Chebyshev filter lies onan ellipse, which can be easily concluded on lookingat the poles formula for both types of filters. (b)Theno of poles required in Chebyshev filter are less, as aresult order of filter is less. This fact can be used forpractical implementation, since the number ofcomponents required to construct a filter of same Where, respectively, a and b are thespecification can be reduced significantly. (c) The numerator and the denominator of the filter transferwidth of the transition band is less in the Chebyshev function which have been z-transformed. And thenfilter. (d)Also multipliers and adders required in convert the result back to the original form:Chebyshev filter are less. x (t) = (e (t) +1)x(1) (6)ALGORITHM FOR DESIGNINGCHEBYSHEV FILTER x (t) is the last filtering result [1]. 1. It finds the lowpass analog prototype poles, zeros, and gain using the cheb1ap function. RESULTS AND DISCUSSIONS 2. It converts the poles, zeros, and gain into Initially a Radar Signal having frequency state-space form. 4.35 * 105 KHz is taken as shown in figure below: 3. It transforms the low pass filter into a bandpass, highpass, or bandstop filter with desired cutoff frequencies, using a state- space transformation. 4. For digital filter design, cheby1 uses bilinear to convert the analog filter into a digital filter through a bilinear transformation with frequency prewarping. Careful frequency adjustment guarantees that the analog filters and the digital filters will have the same Figure 2: A Radar signal 327 | P a g e
    • Richa Gupta, Onkar Chand / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.326-329This radar signal as shown in figure 2 is scaledaccordingly for the fixed SNR i.e.10 dB.Thereafter aGaussian noise is generated and added with the radarsignal because addition of noise improves theprobability of detecting the signal. Figure 5: Magnitude Response of Chebyshev FilterFigure 3: A radar signal with added noise Above figure 5 shows the magnitude response of the Chebyshev filter. From the figure it Figure 3 shows the radar signal with added has been observed that there are ripples in thenoise signal giving SNR of 10.0085dB. This passband and monotonic characteristic in theproduced a radar signal, with Gaussian distribution, stopband .This filter have a smaller transitionzero mean value and a variance of 1. bandwidth which produces smaller absolute errors,For the purpose of removing noise from the signal, faster execution speeds and steeper roll off rate.noisy signal as shown in figure 3 has been passed Results obtained after designing the filterthrough the Chebyshev filter. are: Order of filter (N)=5,Parameters used for designing the Chebyshev filter Normalized Frequency (wn) = 0.0810Hz,are shown in Table 1. Filter Coefficients are: Numerator a = [0.00002919 , 0.0001167,Table1: Parameters for designing Chebyshev filter 0.000175,0.0001167,0.00002919].Fs Sampling Frequency 48000Hz Denominator (b) = [1 , -3.792 ,5.4556 ,F pass Passband Frequency 9600Hz -3.5265,.8640].F stop Stopband Frequency 12000HzApass Passband ripple 1dB Thereafter the noisy radar signal as shown in figure 3Astop Stopband Attenuation 80dB is passed through designed Chebyshev Filter. Pole/Zero Plot 1 0.5 Imaginary Part 4 0 -0.5 Figure 6: A filtered noisy radar signal -1 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 Real PartFigure 4: Pole Zero Plot of Chebyshev Filter Figure above shows the Pole-Zero plot ofChebyshev Filter .Poles of this filter lies on ellipseand minimize the difference between the ideal and Figure 7: A filtered signal with added noiseactual frequency response over the entire passband byincorporating an equal ripple of RP dB in the Figure 7 shows filtered radar signal withpassband. added same Gaussian noise as done in figure 2. Here the noise was added to make comparison between the noisy radar signal and filtered radar signal.SNR measured after adding noise to filtered signal is 10.0615dB which is very high as compared to the SNR (10.0085dB) measured in Figure 3. 328 | P a g e
    • Richa Gupta, Onkar Chand / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.326-329CONCLUSIONS Thus it can be seen that Chebyshev filter isavailable for radar target track smoothing, if wechoose right parameters and transformed the trackdata. In this research, Chebyshev filter has beendeveloped to smooth radar target track and to observethe flight more factually in control center. This ispossible because Chebyshev filters have the propertythat they minimize the error between the idealizedfilter characteristic and the actual over the range ofthe filter, but with ripples in the passband. As theripple increases (bad), the roll-off becomes sharper(good).REFERENCE 1. “Electronic warfare receiving systems”. New York [USA]. Artech House, 1993. 2. Singer R A, Sea R G, Housewright K B. “Derivation and evaluation of improved tracking filters for use in dense multi-target environment”. IEEE Trans. Information Theory.1974, 20(7):423-432. 3. Hu Guangshu. “Digital signal processing- theory, arithmetic and realization”. Publish house of Qinhua University, Beijing 2003. 4. Wu Xiao-chao, Wang Guo-liang, Fang Li- xin, Yan Liao-liao “Application of Butterworth Filter in Display of Radar Target Track”. 2010 International Conference on Measuring Technology and Mechatronics Automation 5. Nitish Sharma, “Preprocessing for Extracting Signal Buried in Noise Using LabView, thesis report Thapar University, 2010. 329 | P a g e