The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed income applications. We investigate if the unscented Kalman filter should be used to capture nonlinearities, and compare the performance of the Kalman filter to that of the particle filter. We analyze the cross section of swap rates, which are mildly nonlinear in th...

This paper analyses the velocity estimation of a target, from the Doppler filter using 1) Kalman filter 2) Adaptive Kalman filter 3) Kalman filter with state vector fusion 4) Adaptive Kalman filter with state vector fusion 5) State vector fused adaptive Kalman filter. Simulation through MATLAB gave good response for 4 and 5 algorithms under low signal to noise ratio. 2 and 3 algorithms gave bet...

State estimation is the common problem in every area of engineering. There are different filters used to overcome the problem of state estimation like Kalman filter, Particle filters etc. Kalman Filter is popular when the system is linear but when the system is highly non-linear then the different derivatives of Kalman Filter are used like Extended Kalman Filter (EKF), Unscented Kalman filter. ...

As Kalman filter technology has better performance for estimation and prediction of dynamic signal, it is gradually used in GNSS signal tracking. According to the steady-state error, transfer function and equivalent noise bandwidth of Kalman filter and traditional loop in steady status, the tracking performance of these two methods is compared in theory. The theoretical analysis demonstrates th...

-For the rapid development high-speed railway system, improvement approach of the velocity measurement accuracy has been studied based on multiple speed sensors on high-speed train. In this method, the velocity measurement data from multi-channel speed sensors were dealt through data fusion of arithmetic mean filter, weighted arithmetic mean filter, Federated Kalman filter and adaptive Federate...

nowadays with increasing use of numerous nonlinear loads, voltage and current harmonics in power systems are one of the most important problems power engineers encounter. many of these nonlinear loads, because of their dynamic natures, inject time-varying harmonics into power system. common techniques applied for harmonics measurement and assessment such as fft have significant errors in presen...

futures contract is one of the most important derivatives that is used in financial markets in all over the world to buy or sell an asset or commodity in the future. pricing of this tool depends on expected price of asset or commodity at the maturity date. according to this, theoretical futures pricing models try to find this expected price in order to use in the futures contract. so in this ar...

this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

in many autonomous mobile applications, robots must be capable of analyzing motion of moving objects in their environment. duringmovement of robot the quality of images is affected by quakes of camera which cause high errors in image processing outputs. in thispaper, we propose a novel method to effectively overcome this problem using neural networks and kalman filtering theory. thistechnique u...