Beamforming Methodology Of Airborne Distributed Phased Array

With the rapid development of radar technology, photoelectric technology and digital technology, the performance of airborne equipments has a wonderful development in the 21 st century. Detection range is improved significantly in Radar. At the same time, these equipments gain better sensitivity, higher resolution ratio and less weight. Especially in military field, the air communication is especially important.Among the communication antennas, the phased-array antenna is a common choice.The distributed phased-array antenna can skillfully divide the phased array with a large diameter into several phased sub-arrays with a small diameter. In terms of airplanes,every phased sub-array can be installed in different positions of airplane wings, which can, on the one hand, ensure the gains of antenna without influencing the pneumatic requirements of airplanes, on the other hand, skillfully solve the antenna installation on airplanes. Therefore, research into the distributed phased array is of vital significance to airplanes’ antenna design. This paper mainly studies the beamforming methods of the onboard distributed phased array in the following four aspects:The general esign methods for phased sub-arrays is investigated. We study the phased array principles and define various basic parameters of the antenna, including the directional diagram, the beam scope, the directionality and gains. Analyze the signal model of the phased array antenna, learn and analyze its indexes and design an even plane sub-array for the onboard phased array.A method for angular correction is proposed. Since every sub-array is installed on airplane wings, the deformation of wings will change the angle of every array to the satellite or ground station. Certain method should be conducted to calculate the direction of arrival(DOA) of the signal on every array. Thus, a coordinate transformation method is put forth for angular correction, conduct experimental simulation of the correction method, and verify its correctness.The signal synthesis method for multiple sub-arrays is studied. The purpose of signal synthesis is to rectify the time delay difference of signals output by every sub-array. After that, all the signals can have in-phase superposition, thus further improving the SNR of signals. The self-adaptive filtering method is adopted to finish the signal synthesis through weighted sum. The synthesis methods for different signals are not the same. Signal synthesis with the input of same SNR can be divided into twotypes. One is to improve the signal synthesis with the input of high SNR and the other is the signal synthesis with the input of low SNR. In terms of signals with the input of higher SNR, the self-adaptive LMS filtering algorithm based on the power inversion rules can be adopted to achieve signal synthesis. In terms of signal synthesis with the input of low SNR, the antenna array method for the deep space communication can serve as a reference. Thus, SUMPLE algorithm is adopted. The chosen method is adopted for experiment simulation to verify its feasibility. The signal synthesis with the input of unequal SNR calls for two weightings of the multichannel data before their sum.The first weighting algorithm is similar to that of the signal synthesis with the input of same SNR. SUMPLE algorithm is adopted to calculate its weight vector, and correct the time delay difference of every sub-array to output signals so that multi-channel data output by the first weighting can have in-phase superposition. The second weighting adopts the spectrum estimation of SNR of every channel of data. Then, through the maximal ratio synthesis algorithm, the weighting sum is adopted. The experimental simulation is conducted to verify the feasibility of the method.The antenna pattern is illustrated through computer simulation. Every sub-array finishes beamforming through two methods, respectively. One is without the angular correction, the other is with the angular correction. Similarly, signal synthesis can be divided into two types. One type is that every sub-array outputs the same SNR but the SNR value is large. The signal synthesis adopts the PI algorithm based on the useful signal. The other type is that every sub-array outputs unequal SNR, and SUMPLE algorithm is adopted to correct the time delay. Based on the SNR estimation and the maximal ratio synthesis algorithm, the signal synthesis is conducted. The overall system directional diagram is observed to verify the feasibility of the system.