Adaptive Digital Beamforming Technology Rasearch

1980s, the advent of digital integrated circuits, microwave technology, signal processing technology development and progress, the digital beamforming technology, adaptive technology began in phased array radar has been applied. Compared with the traditional mechanical scanning radar, phased array radar has a large power-aperture product, the role of distance; multi-beam forming capabilities, expanding the scope of observation radar airspace, to achieve the multi-target detection and tracking. Application of adaptive digital beam radar beam is increased agility ability to effectively implement adaptive spatial filtering and space-time adaptive processing, effective suppression of active interference. To meet the design requirements of multi-functional, large phased array radar picket the large number of complex hardware systems, computational complexity is very high. In the case without affecting system performance, cost control and effective way to reduce the computational complexity: the array of sub-array partitioning technique is a digital phased array radar primary problem.In this paper, under the premise of a narrowband signal linear array and planar array digital beam received signal model to analyze the optimal beamforming three basic guidelines:minimum mean square error (MSE) criterion, the maximum signal to noise ratio (SNR) standards, linearly constrained minimum variance (LCMV) criterion, under certain circumstances, all three criteria are equivalent, depending on the specific application is required to determine the appropriate conditions known best practices. Subarray uniform division of non-uniform sub-array divided into overlapping subarrays theoretical performance adaptive beamforming studied the characteristics of a uniform division of sub-array lobes and a gate and a gate zero occurs conditions into non-uniform characteristics subarray put forward the principle of division of sub-arrays. Simulation and Analysis of the digital beamformer receiver technology. For adaptive beamforming sample matrix inversion (SMI) algorithm, recursive least squares (RLS) algorithm, the minimum mean square error (LMS) algorithm principle and algorithm flow diagram conduct research and online array and planar array case for three algorithms for simulation analysis and comparison, to analyze the performance of different algorithms, focus on the diagonal loading technique SMI algorithm performance.