Target detection with beamforming

Target detection is almost used in any area of life as scientific study, security and medical. There are a lot of methods for target detection with using array structure. Beamforming is the most widely used technique. Beamforming is signal processing technique for adding steering to signal with using array structure when transmit or receive. Beamforming is used in RADAR, SONAR, radio communication, seismology, astronomy, smart antennas and medical diagnostic systems. There are application areas in LASER systems, speech signals and underwater communication. Beamforming is firstly used in RADAR systems with phased array antenna during World War II. After a while it was used in SONAR systems. Beamforming can be achieved with data independent, statistically optimum, adaptive and partial adaptive methods. In recent years, investigations has been concentrated on areas that are cost effective, fast computation, low energy consumption, sharpening target detection, detection of targets in strong reverberation environment. Nowadays, researches in cancelling side lobes, minimization interference, MIMO antennas and time-frequency analyses are ongoing. In this thesis, target is assumed to be detected by SONAR simulation. Target detection outputs are obtained time and frequency domain beamforming methods. Target data generation and beamforming programs are produced in MATLAB. Underwater environment used in beamforming is described. Linear and planar arrays are scrutinized. Windowing, steering and aliasing are discussed. Planar array is used for increasing SNR and 3D scanning. Time and frequency domain beamforming methods are inspected for different SNR values. Target detection performances are observed and compared. Goertzel algorithm is proposed to be used in frequency domain beamforming at low SNR values. It is observed that Goertzel algorithm can enhance target detection performance at low SNR.