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              Mekhatronika, Avtomatizatsiya, Upravlenie, 2017, vol. 18, no. 8, pp.  571—576 
              DOI:  10.17587/mau.18.571-576 
               
              Algorithm for Estimating  the Parameters of Sea Pitching for Increasing the Accuracy of a Ship-Borne  Radar Beam Positioning 
              A. N. Grachev, ga150161@mail.ru, Tula State University,  Tula, 300012, Russian Federation, S. A.  Kurbatsky, qrbs@rambler.ru, Yu. I. Lebedenko, lebedenko@tsu.tula.ru, Central Design  Bureau of Apparatus Engineering, Tula, 300034, Russian Federation
               
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            Corresponding author: Grachev Aleksandr N., Associate Professor,  Tula State University, Tula, 300012, Russian Federation, e-mail: ga150161@mail.ru             
              Received on September 12, 2016  
                Accepted on December 16, 2016 
              The sea waves cause the effect of a  rotational motion (i.e., pitch, roll and heading angle) of ships. The ship  rotational motions result in beam pointing error of the phased array radar  aboard the ship. The antenna stabilization aimed to achieve a beam pointing  accuracy over a long dwell time is an important problem for the shipborne  phased array radars. Due to the dynamic and stochastic nature of the sea  environment, the shipborne phased array radar must be able to compensate for  the ship's motion adaptively. In this paper, the linear discrete Kalman filter  is proposed as a predictor for the shipborne phased array radar, which can  compensate for the beam pointing error and track the air and sea surface  targets. The pitch, roll and heading angles and the its velocities data are measured  on-line from a gyroscope of the sea vehicle and used from the ship motion  mathematical models for their prediction. It is proved, that the pitch, roll,  and heading motion models may be considered as independent. All these models  are presented as the same second order linear differential equations with  different parameters. Besides, equivalent linear discrete state space models  for the angles' changes are constructed in the paper. The estimation accuracy  of the Kalman filter (predictor) depends on the values of different parameters,  such as the parameters of the ship's motion mathematical model, measurement  error covariance matrices, etc. The sea environments are very dynamic, hence,  there is a need for an adaptive system for the controlling and compensating  devices, operating regardless of the ship's motion. Continuous monitoring of  the environment and adapting filter ensure parameters with less computational  burden needed for a real time application. The paper describes a technique for  identification of such parameters by the measured correlation functions of the  pitch, roll, and heading angles. Finally, it is proved by the computer  simulations that the proposed compensations technique is a real time applicable  algorithm for a shipborne phased array radar. The computer simulation was  performed with the following parameters: the measurement frequency for the  gyroscopes was 100 Hz, the prediction times of the Kalman filter were 0.01 s  and 0.1 s. The following two cases were considered. In the first case, only the  predicted angles were measured with gyroscopes. In the second case, the angles  and the rates of their change were measured. The simulations demonstrated that  the presented prediction algorithm ensured higher accuracy (less root mean  square errors of the predicted angles) than the initial accuracy of the  gyroscopes measurements. 
              Keywords: shipborne phased array  radar, ship rotational motion, pitch, roll, and heading angle, beam pointing  error compensation, parameters identification technique, linear discrete Kalman  filter               
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            For citation:
             
              Grachev A. N., Kurbatsky S.  A., Lebedenko Yu. I. Algorithm for Estimating the Parameters of Sea Pitching for Increasing  the Accuracy of a Ship-Borne Radar Beam Positioning, Mekhatronika, Avtomatizatsiya, Upravlenie, 2017, vol. 18, no. 8,  pp. 571—576. 
                 
DOI: 10.17587/mau.18.571-576 
               
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