A Novel Adaptive Beamforming for Radar Systems

Transcription

1 International Journal of esearch and Innovation in Applied cience (IJIA) Volume I, Issue IX, December 26 IN A Novel Adaptive Beamforming for adar ystems wathi harma, ujatha. 2 PG tudent, Department of TCE, CMIT, Bangalore 2 Associate Professor, Department of TCE, CMIT, Bangalore Abstract: - Modern adars use phased array antenna for higher directive gains. These array antennas can be used to form a beam in the desired direction also nown as beam steering, if there is any jammer present then it cannot be suppressed by just beamforming or beam steering, in such case we need to use Adaptive antenna. Adaptive antennas use the smart signal processing algorithms also nown as adaptive algorithms. Adaptive beamforming is used to place a deep null in the direction of the Jammer, identify the spatial signals eywords: Direction of Arrival, Adaptive beamforming I. INTODUCTION adar is an object detection system that uses adio signals to determine ange, Velocity, and angle of the object. It is used to detect aircraft, ships, guided missiles, motor vehicles, weather formations. With the use of Phased array antenna the beamforming gain can be maximized while minimizing interference. Phased array antenna can be used in adars to form a beam in the desired direction and supress the interference (clutter noise jammer) An antenna array is a structure that is composed of more than one radiating element that are fed with a specific amplitude and phase. The radiating elements can be arranged in four types viz Linear, Circular, Planar and Conformal. Multiple radiating elements synthesize the radiation characteristics that cannot be achieved by a single radiating element and also help to achieve high directivity and gain. In Phased array antennas by controlling the increasing phase difference between the elements the maximum radiation can be achieved in any desired direction [. Phased array antennas match the radiation characteristics to the desired coverage area, the radiation pattern can be electronically changed by controlling the phase and amplitude. Phased array antennas are used in communication and adar and they offer of benefit of beam shaping and steering for specific active operation conditions, they are specifically used in adaptive radar systems and in pace Time Adaptive Processing (TAP). In addition to the main function of transmit and receive the adaptive array antenna need to fulfil a. Direction of Arrival estimates: In order for the adaptive antenna to provide required functionality they need to be able to detect the direction of arrival of the incoming signals using the DOA algorithms. This information received by the antenna array is passed to the signal processor for the analysis. b. Beam steering:with the DOA of the incoming signal the control circuitry in the antenna will be able to optimize the directional beam pattern of the adaptive array. ence we can say that in Adaptive Array antenna the sensors elements (antenna) are arranged in the form of an array and a processor which will calculate the weights to adapt and suppress the interference. As soon as the processor is given a beam steering command, it samples its current environment calculates the weight towards optimization of output N and proceeds to adjust the weight of each element. The antenna beam from the adaptive antenna array shows the flexibility to be designed as needed, a null can be placed in the direction of the Jammer where as the main beam is left unaltered [3. II. TEOETICAL CONIDEATION Beamforming also nown as patial filtering is a signal processing technique used for directional signal transmission and reception. There are two types of beamforming i.conventional Beamforming ii.adaptive Beamforming. 2. Conventional beamforming: The beamforming (spatial filtering) operation can be decoupled into two sub processes. i. ynchronization: This process is to delay or advance each sensor output by a proper amount of time so that the signal coming from the desired direction are synchronized. ii. Weight and um: In this step the received signal is aligned and weighted and then all the result are added together to form one output. ynchronization controls the steering direction and the weight and sum part controls the width of main lobe and the characteristics of the side lobe. The direction in which the beam is steered is called the loo direction. In the below figure is the angle of incidence of the wave-front with respect to the array normal. If is the phase offset that accounts for phase at n= element, then single sample formed by individual element at time is given by [6 ) = A* j[ ( t ndsin/ c) y [ n = y ( t e () n Y = [ y[ y[ y[2 y[ N (2) Page 27

2 International Journal of esearch and Innovation in Applied cience (IJIA) Volume I, Issue IX, December 26 IN Y Figure : Conventional Beamforming Figure 2: Wavefront impinging on an ULA = A[e = A[e j2dsin/ j... e... e j2 ( N ) dsin/ j2( N ) = Aa ( ) (3) s where = 2 ndsin / is the spatial frequency and a ( ) is the spatial steering vector Conventional non adaptive beamforming is implemented as a weighted sum of element signals. Z = h y, where h is the vector of complex weights s 2.2 Adaptive beamforming: Adaptive beamforming is a technique in which arrays of antennas are used to achieve maximum reception in the direction of desired user while signals of same frequency from other directions are rejected. This is achieved by varying the weights of the each of antennas used in the array. A smart antenna system combines multiple antenna elements with a signal- processing capability to adjust its radiation and or reception pattern automatically in response to the signal environment. Multiple antennas have ability to enhance the capacity and performance without the need of additional power or spectrum [. Adaptive array antenna systems are currently the subject of intense interest and investigation/development for radar and communications applications. The principal reason for the interest is their ability to automatically steer nulls onto undesired sources of interference, thereby reducing output noise and enhancing the detection of desired signals [2. There are many algorithms to implement Adaptive filters i.e. LM (Least Mean quare), L (ecursive Least quare), MI (ample Matrix Inversion). III. POPOED ALGOITM The direction of the signal is detected by the Direction of Arrival algorithm, here Music algorithm is used. For Adaptive beamforming the sample matrix algorithm is commonly used in adaptive arrays since it offers maximum convergence to the maximum signal-to-interference-plus-noise ratio (IN). This method is also alternatively nown as direct method inversion (DMI). It is a time average estimate of the array correlation, matrix using -time samples. If the random process is ergodic in the correlation, the time average estimate will equal the actual correlation matrix [3. h = [ w w... w N j j2( N ) e [e... e (4) h = w e ( ) (5) a s where the symbol e represents the adamard product of two vectors. If the array is steered to angle. The response of the beamformer steered at to an incoming wavefront at N j( ) n Z( ) = h y = A ( e ) (6) n= Figure 3: MI Algorithm for Adaptive beamforming Wiener olution gives the optimum array weights which is given by = r (7) Page 28 F opt

3 International Journal of esearch and Innovation in Applied cience (IJIA) Volume I, Issue IX, December 26 IN Where r = E[ d * = E[. The correlation matrix can be estimated by calculating the time average such that = = ( ) (8) where is the observation interval. The correlation vector r can be estimated by r * = d ( ) (9) = This approach is used for -length bloc of data and hence is nown as bloc-adaptive approach. We thus adapt the weights bloc by bloc. The matrix () is defined as the ranging over -data snapshots. ( ) = 2 M ( ) ( ) ( ) (2 ) (2 ) 2 th bloc of x vectors where is the bloc number and is the bloc length. The estimate of the array correlation matrix is given by: 2 M ( ) ( ) ( ) () IV. IMULATION EULT The Conventional beamforming, for Linear and Planar array are simulated. Below Present is the imulation result of Planar array. Conventional Beamforming imulation Parameters: Array size: 8X8 Distance between elements: /2 Frequency: 3e9 AOA=teering angle=[2;5 Figure 4: Beam teering Azimuth cut at 4 = [ In addition, the desired signal vector can be defined by () d = [ d( ) d(2 ) d( ) (2) Thus the estimation of the correlation vector is given by r( ) = [ d * The MI weights can then be calculated for the length as F MI = [ r( ) (3) th bloc of (4) Figure 5: Beam teering Elevation cut at As shown in the figure 4 and 5 the beam is steered to angle 4 and Page 29

4 International Journal of esearch and Innovation in Applied cience (IJIA) Volume I, Issue IX, December 26 IN Figure 6: Input to the beamformer excluding noise and Jammer Figure 9: AOA same as steering angle [4 ; and Jammer at[ ;6 As seen in the figure 8 and 9 the conventional beamformer cannot supress the jammer. Adaptive Beamforming imulation Parameters: ampling frequency: 24 Gz Array size: 8X8 Angle of Arrival (desired angle): [5; Frequency: 3Gz Figure 7: Input to the beamformer with noise and Jammer Angle of Jammer: [2; 2 Figure : Input signal without noise and jammer Figure 8: AOA same as steering angle [4 ; with no jammer and noise Page 3

5 International Journal of esearch and Innovation in Applied cience (IJIA) Volume I, Issue IX, December 26 IN Figure : Input signal with noise and jammer Figure 2: Conventional Beamformer output Figure 3: Output from Adaptive Beamformer From the figures 2 we can see that the output from beamformer is not free of Jamming signal after adaptive processing the MI Algorithm output is as shown in figure 3 Conclusion V. FUTUE COPE AND CONCLUION Conventional beamforming is used in phased array antenna to form a beam in a particular direction. When the signal that is received by the array consists of clutter, noise and jammer signals the desired signal cannot be distinguished with the jamming signal and the required data cannot be interpreted. In this case Adaptive beamforming is used which will suppress the noise and clutter and place a null in the direction of the Jammer. There are many algorithms that can be used to implement adaptive beamforming they are LM, L MI etc. ince the convergence rate of MI is faster and the weight calculation complexity in MI is less than LM and L we use MI algorithm here, as in adar applications the weight calculation for Adaptiveness should be robust and with fast convergence. Future cope In adar, the clutter (zero Doppler) is separated from the Moving target using the moving target indication filtering, which removes the clutter content and passes remaining side lobe return and altitude return. For low moving targets (most moving targets are "slow" or low Doppler targets, either they are slow or exhibit a low Doppler due to their motion direction. For radar on a satellite ( m/s) all targets near the ground (jet aircraft 3 m/s) are slow targets). The target return is so low that the returns from them is embedded in the main lobe clutter (zero Doppler) and cannot be separated by conventional Moving Target Indication (MTI) technique. To overcome this, we use a technique called pace Time Adaptive Processing(TAP). EFEENCE [. C. A. Balanis, Antenna theory: analysis and design. John Wiley & ons, 26. [2.. Cox,. Zesind, and M. Owen, obust adaptive beamforming, IEEE Transactions on Acoustics, peech, and ignal Processing, vol. 35, no., pp , Oct [3. W. F. Gabriel, Adaptive arrays ;An introduction, Proceedings of the IEEE, vol. 64, no. 2, pp , Feb [4. L. L. orowitz,. Blatt, W. G. Brodsy, and. D. enne, Controlling adaptive antenna arrays with the sample matrix inversion algorithm, NAA TI/econ Technical eport A, vol. 8, pp , Nov [5. D. undu, Modified MUIC algorithm for estimating DOA of signals, ignal Processing, vol. 48, no., pp. 85 9, Jan [6. Mar A. ichards, Fundamentals of adar ignal Processing. McGraw-ill Professional, 25. [7. P. etlur and M. angaswamy, Waveform Design for adar TAP in ignal Dependent Interference, IEEE Transactions on ignal Processing, vol. 64, no., pp. 9 34, Jan. 26. [8. W. L. tutzman and G. A. Thiele, Antenna theory and design. John Wiley & ons, 22. [9.. A. Vorobyov, A. B. Gershman, and Z.-Q. Luo, obust adaptive beamforming using worst-case performance optimization: a Page 3

6 International Journal of esearch and Innovation in Applied cience (IJIA) Volume I, Issue IX, December 26 IN solution to the signal mismatch problem, IEEE Transactions on ignal Processing, vol. 5, no. 2, pp , Feb. 23. [.. Wang and L. Cai, On adaptive multiband signal detection with the MI algorithm, IEEE Transactions on Aerospace and Electronic ystems, vol. 26, no. 5, pp , ep. 99. [. X. Zhang, L. Xu, L. Xu, and D. Xu, Direction of Departure (DOD) and Direction of Arrival (DOA) Estimation in MIMO adar with educed-dimension MUIC, IEEE Communications Letters, vol. 4, no. 2, pp. 6 63, Dec. 2. [2. M. Zhou, X. Zhang, X. Qiu, and C. Wang, Two-Dimensional DOA Estimation for Uniform ectangular Array Using educed-dimension Propagator Method, International Journal of Antennas and Propagation, vol. 25, p. e48535, May 25. [3. G.. eddy and V. A. Pillai, A tudy of ample Matrix Inversion Algorithm for mart Antenna Applications, Indian Journal of cience and Technology, vol. 9, no. 5, Page 32