INVESTIGATIONS INTO BEAM STEERING ALGORITITHMS FOR ADAPTIVE ANTENNA ARRAYS BY Siyandiswa Juanitta Bangani Supervisor: Dr R.Van Zyl Cape Peninsula University of Technology MTECH/MSC F’satie

OUTLINE Objective Approach Algorithms under investigation Simulations Classical (Conventional) Beamformer Capon’s Beam former MUSIC Algorithm Least Mean Square (LMS) Simulations Discussions of results Conclusions Questions © CSIR 2006 www.csir.co.za

OBJECTIVE The main objective of the research is on directing the beam towards the desired target in a particular direction while successfully rejecting all other targets in unwanted directions The research is based on direction of arrival estimation and adaptive beamforming © CSIR 2006 www.csir.co.za

Objective Cont. Desired Target direction Interference direction © CSIR 2006 www.csir.co.za

Approach Receive: Transmit: Two aspects to the research Direction of arrival algorithms (DOA) to locate targets Transmit: Mechanism to steer main beam in required direction Linear phase shifting Weighted phase shifting © CSIR 2006 www.csir.co.za

Receive: Beamformer- DOA Beamforming Block diagram measurement and storage of element signals multiplication by weighting factors and addition for all directions calculation of output power yy* searching for maximum output power as a function of direction direction for maximum power = bearing weighting factors for all directions u y=wHu w* © CSIR 2006 www.csir.co.za

Classisal and Capone’s Beamformer In the classical beamforming approach for DOA estimation, the beam is scanned over the angular region of interest in discrete steps by forming weights w=a(Ø) for different Ø and the output power is measured The technique uses some of the degrees of freedom to form a beam in the desired look direction, while simultaneously using the remaining degrees of freedom to form nulls in the direction of interfering signals. Capon's method requires the computation of a matrix inverse, which can be computationally expensive for large antenna arrays. © CSIR 2006 www.csir.co.za

MUSIC Algorithm MUSIC algorithm is a high resolution MUltiple SIgnal Classification technique based on exploiting the eigenstructure of the input covariance matrix. Provides information about the number of incident signals, DOA of each signal, strengths and cross correlations between incident signals, noise power, etc. © CSIR 2006 www.csir.co.za

Beamforming-DOA Cont. Classical beamformer / Conventional beamformer Capon’s Beamformer MUSIC Algorithm © CSIR 2006 www.csir.co.za

DOA simulations Effect of SNR Proximity SNR=20 θ = (440 and 510) © CSIR 2006 www.csir.co.za

TRANSMIT: Steering Mechanism Electronically steering by adapting the phases Generating look up Table in FEKO Linear phases Weighted phases © CSIR 2006 www.csir.co.za

Linear phases -generated for Direction determination Phi (Ø) Theta (θ) Gain (dB) 3dB BW (degrees) Main side lobe suppression 700 650 11.70 140 -12dB 800 11.78 170 -13dB 900 600 11.74 130 1000 500 10.50 16 0 -5dB 1400 400 10.43 200 -12.5dB 150 0 300 10.15 -14dB 160 0 250 9.97 -3dB 1700 9.84 620 -1.5dB 1800 00 9.91 0dB © CSIR 2006 www.csir.co.za

Linear phase shifting and Weighted phase Shifting 3D RADIATION GAIN PATTERN © CSIR 2006 www.csir.co.za

Cont. -5dB -13dB Cartesian plot 1000 linear phase shift 1000 weighted phase shift -5dB -13dB Cartesian plot © CSIR 2006 www.csir.co.za

Discussion of Results MUSIC algorithm gives better results as compared to the Classical and Capons beamformer The LMS algorithm improves the short comings of linear phase shift especially when it comes to radiation characteristics In improving the linear phase shift there is a trade off between desired direction and main side lobe level © CSIR 2006 www.csir.co.za

CONCLUSIONS In conclusion with the various simulation performed the algorithms investigated show possible results to realise the objective The combination of MUSIC algorithm for identifying DOA and LMS adaptive beamformer gives positive results © CSIR 2006 www.csir.co.za

Thank you ? © CSIR 2006 www.csir.co.za