The main task of the study is to estimate the position Error in an inertial navigation system by integrating it with the visual system. The case study is a spacecraft that must accurately measure its position relative to a predetermined landing point. The spacecraft is assumed to be augmented GNSS navigation. Therefore, when satellite signals are dropped out or when landing on a moving marine platform, the data of the vision navigation system replaces the information of the satellite navigation system and improves the accuracy of the spacecraft navigation system. An Extended Kalman filter has been used to integrate inertial and vision navigation system information. In addition, the output data of the vision system, in order to be used in the Kalman filter measurement equations, is first processed by the recursive least square filter. The relevant relations are given and based on the results of software simulation, the efficiency of the proposed method is shown.

CNC machine tools are widely used to produce precise parts through executing expensive operations. In precision machining, the machine tool's geometrical and kinematical Errors cause geometrical and dimensional deviations in vital features of machined parts. Kinematic modeling of a machine tool structure can help to predict the real value of the overall tool positioning Error. In this paper, modeling of three-axes CNC machine tools has been considered. The developed model can simply be used for all kinds of linear axes configurations, like three-axes CNC machine tools. The model can be useful for a large variety of applications, including software based Error compensation systems and prediction of the real shape of parts after being machined or measured by Error contained CNC or CMM machines. Experimental tests were conducted to validate the model. Analytical Estimations were shown to be in good accordance with experimental tests.

This paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. Then numerical results and Error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. Finally an example is given to illustrate the performance of the methods.

Time Reversal (TiR) technique mitigates the complexity of receiver in UWB indoor channels, but is very sensitive to the channel Estimation Error. The effect of channel imperfection on TiR technique is considered in this paper. At first, the Bit Error Probability (BEP) of the TiR-UWB communication system under the assumptions of the simple Matched Filter (MF) receiver with the channel Estimation Errors is derived in closed-form. Moreover, based on optimal MMSE estimator receiver, a pre-filter is calculated in closed-form to improve the performance of the TiR-UWB system in an imperfect CSI scenario. Furthermore, a two stage iteration-based algorithm is developed at transmitter to calculate a pre-filter in MF receiver. This improved algorithm causes the channel Estimation Error tends to zero in some steps for the TiR-UWB system with MF. The initial value for this iteration-based improved algorithm is considered to be closed form pre-filter calculated in TiR-UWB system with optimal MMSE estimator. Finally, exhaustive simulations are done to demonstrate the performance advantage attained by the improved algorithm.