Research On Structural Response Reconstruction Method Of Active Phased Array Antenna

With the level of science and technology and the military demand continues to improve,the active phased array antenna beam with fast scanning,high speed flexible beam control,signal energy distribution and conversion,adaptive technology is widely used in antenna field.But widely application will lead to the complexity and extreme service environment,coupled with its flexible structure,the antenna array will deform when subjected to external vibration,shock,wind and thermal load,the antenna unit will deviate from the ideal position,the antenna is electrically to deteriorate,so how to shape information in service quickly and accurately obtain the antenna is an important prerequisite to ensure its electrical performance.However,for the active phased array antenna in practical engineering,on the one hand,due to its large structure system,on the other hand,because of its high density integrated complex geometry,it is not possible to monitor the shape information by installing the sensor at each location.For the active phased array antenna during the service how to quickly and accurately obtain the shape information of the antenna,This paper will study from two aspects and three working points.The two major aspects are: First,the measuring point leads to the problem of lack of information,The main structure of the dynamic response of reconstruction theory to explore,in order to get the whole shape information from a few measuring point.Second,for a problem how to reflect the dynamic characteristics of the model a few measuring points as much as possible,studying the optimization of sensor layout.The main three work points are as follows:Based on Bayesian and modal the theory,we put forward the Calman filter response reconstruction algorithm,namely in the presence of model and measurement noise,using Kalman filtering principle updating accurate state structure of the system,so as to calculate the response of the structure required for the position.At the same time,based on the weighted least squares and Kalman filter principle,the mode of Kalman filter reconstruction under unknown excitation was built.In addition to the different parts of the antenna structure deformation mechanism of different situations,we put forward the reconstruction of Multiple types of measurement information,the reconstruction theory is perfect.Finally,we made a simulation based on active phased array antenna,In terms of comprehensive comparisoncomprehensive contrast,regardless of the accuracy,stability and convergence from the point of view,the effectiveness of the method is proven.For the unknown uncertainty of the noise variance and the divergence of the iterative process,the maximum likelihood criterion is used to perform an optimal unbiased estimation of the noise variance.At the same time,the width of the window function makes the estimation result more able to reflect the dynamic characteristics of the noise.Finally,Combined with the Kalman filter principle,the reconstruction model of response adaptive reconstruction of the model noise variance,measurement noise variance and noise variance integrated adaptive Kalman filter is completed,making it more valuable for engineering applications.In addition,the length of the panel is 2880 mm,width is 1728 mm,the horn hole is 32*8,the length and width of the hole is 72 mm,the material elastic modulus is 70e3,the Poisson's ratio is 0.3,the density is 3.72*2700e-12,and the load is the antenna The model is simulated and verified.From the results,it can be seen that the modal reconstruction error is up to 60.8%.At the same time,there is no pre-adaptive error of 4.1%,and only 2.1% after adaptive.In order to be more persuasive,the above antenna model was verified by physical experiments,and the bending and torsion conditions were simulated.The results show that the modal reconstruction error is at most 4.6%,while the adaptive error is 2.2%.Both the simulation results and the experimental results prove the correctness and effectiveness of the adaptive Kalman filtering reconstruction model.The reconstruction error caused by model and measurement noise is described by uncertain parameters.Based on information entropy theory,the contribution of different locations to the stability of the entire structural system is described,and the sensor optimization layout model based on information entropy is obtained.Combining the state space equations of modal theory to simplify the above model,the final optimization objective function is obtained.On this basis,the sequence optimization algorithm is given by analyzing the characteristics of the objective function.Finally,based on the above antenna model,in the case of the same load and the same number of sensors,this chapter compares the optimized sensor layout model with the genetic algorithm.From the perspective of the reconstruction accuracy,the maximum error of the genetic algorithm is 1.9%,and the method of this paper is only 1.1.%,from the calculation time point of view,this method requires only 2s,while the genetic algorithm requires 146 s,and for the same two positions,the unreconstructed reconstruction errors are 2.1% and 1.2%,respectively,and the reconstruction error after optimization decreases.1.3%,0.6%.From the above results,we can see the effectiveness of this model.