Research On The Algorithm Of Vehicle State Testing System Based On GF-INS And GPS

Measurement of vehicle state information is the fundmental problem on researchand design of vehicle handling and stability. On the other hand, it also is the maincondition of implementation on vehicle electric and Intelligent Driver-Assisted. Sothat it is very important for all to how to acquire the veracious vehicle stateinformation.The main research content is :First,we examine the feasibility of designing an inertial navigation system that usesonly accelerometers to compute the linear and angular motions of a rigid body. Theaccelerometer output equation is derived to relate the linear and angular motions ofa rigid body relative to a fixed inertial frame.A sufficient condition is given to exa-mine if a configuration of accelerometers is feasible. If the condition is satisfied,theangular and linear motions can be computed separately using two decoupled equa-tions of an input-output dynamical system.a state equation for angular velocity andan output equation for linear acceleration.This simple computation scheme is deri-ved from the corresponding dynamical system equations for a special cube config-uration for which the angular acceleration is expressed as a linear combination ofthe accelerometer outputs. The effects of accelerometer location and orientationerrors are analysed. Algorithms that identify and compensate these errors are deve-loped.Secondly,a gyroscope-free inertial navigation system uses only accelerometers tocompute navigation trajectories. It is a low-cost navigation system, but its outputerror diverges at a rate that is an order faster than that of a conventional gyroscopebased system. So integration with an external reference system, such as the GlobalPositioning System, is necessary for long-term navigation applications. In thispaper,an integrated GPS and gyroscope-free INS system is designed to achievestable long-term navigation. The linear and nonlinear error models of agyroscope-free INS are derived and are used as Kalman filter equations to estimatethe errors in the gyroscope-free INS data. The effects of gyroscope-free inertialmeasurement unit errors are also analyzed. By using computer simulations, theperformance of the integrated GPS and gyroscope-free INS system is verified.Third, the simulating experimental validates correctness of the kernel algorithm ofintegration navigation system. The navigation system incorporates a strapdowninertial navigation system with the global positioning system. The implementationis referred to as a kalman filter. The error estimator is implemented by a kalmanfilter based on the linearized error dynamics. The state estimator has apredominantly result. Subtracting the error estimate from the inertial navigationsystems output, in a well designed system, produces an accurate estimate of thenavigation state.The forth, experimental validates of the integrated GPS and gyroscope-free INSsystem. We verify the algorithm by doing experiments in our experimental vehicle.In the experiment, we run the vehicle in several model condition,(for examplecircle, right-angle, snake, linechange),newsreel the real-time vehicle conditioninformation ,last deal with the data.The meaning of the article is :This paper presents three important research issues. The first is the navigationequations of a Gyro free INS that is based on the tangent plane coordinate. Thesecond is error equations of the proposed strap-down GF-INS. The third is a novelmethod for the integration of theGF-INS and the GPS.