Research On Ship Heave Measurement Technology Based On Inertial Navigation System

As the ship becomes more and more important in human life and development,engineering requirements of ship motion precision and reliability are increasingly high,accurate ship heave information can effectively compensate the heave motion,reduce ship heave motion,keep the ship steady on the sea and improve ship's safety,operational efficiency and operational capability,therefore,the measurement of ship heave information has very important practical significance and engineering value.Firstly,this paper defines the coordinate system and the Conversion between coordinates,the working principle and the navigation calculation process of the strapdown inertial navigation system are introduced.Subsequently,the error characteristics of vertical acceleration information of strapdown inertial navigation equipment are analyzed.Finally,the construction of the experimental environment of the heave platform is introduced,which provides data support for the heave algorithm proposed below.Secondly,the heave filter based on digital filtering technology is introduced,around the phase problem of the heave filter's output,this paper proposes improved heave filter based on optimal design and improved heave filter based on phase compensation,the main idea of the former is moving zero point of the heave filter's transfer function,the error function of the modified transfer function is used as the objective function,the parameter of the transfer function can be obtained by minimizing the objective function,this method achieves high accuracy heave measurement and is easy to implement,but its output is easily affected by low frequency and noise,so this method has limitations;the main idea of the latter is increasing the cutoff frequency of heave filter to suppress the effect of noise and bias,estimating input's frequency by frequency estimation algorithm,according to the estimated frequency,an adaptive FIR filter is designed to achieve the phase correction of the output,this method achieves high accuracy heave measurement,but its output accuracy is very dependent on the effect of frequency estimation.In order to avoid the phase problem of digital filtering,a method of ship heave measurement based on Kalman filter is proposed in this paper.This method establishes ship's heave position,velocity and acceleration models and constructs the Kalman filter,heave measurement information can be obtained by superimposition of position state quantities,due to Kalman filter depends on model's frequencies,frequency spectrum refinement algorithm is introduced.This methon has no phase problem of digital filter and is not sensitive to noise bias,high accuracy of heave information can be obtain,but this method depends on the precision of frequency estimation,because of hysteresis of frequency spectrum refinement algorithm,this method has limitations.A ship heave measurement method based on adaptive filtering is proposed to overcome the limitations of the above algorithms.This method adopts heave filter of high cut-off frequency to suppress the influence of noise and bias,the adaptive algorithm is used to model the output of the heave filter,and the output model is corrected to solve the phase problem of the output,in addition,the selection of parameters in the adaptive algorithm is also analyzed.This method does not exist the limitation of frequency estimation and can solve the phase problem of heave filter,high-precision heave information can be obtained,but the computational complexity of the method is large.Finally,this paper further analyzes the various algorithms,discusses the ideas and methods to solve the problem.Then the difference between the frequency estimation algorithms in the paper is discussed and the establishment of the frequency point model in the adaptive algorithm is analyzed.The performance and limitations of the algorithm are compared from all aspects.Considering all aspects,this paper proposes the method based on adaptive filtering technology,its output precision is high,the external noise influence is small and it does not depend on the frequency estimation algorithm.