The gyroscope and accelerometer are the basic sensors used by most Unmanned Aerial Vehicle (UAV) like quadcopter to control itself. In this paper, the fault detection of measured angular and linear states by gyroscope and accelerometer sensors are present. Uncertainties in measurement and physical sensors itself are the main reasons that lead to generate noise and cause the fault in measured states. Most previous solutions are process angular or linear states to improving the performance of quadcopter. Also, in most of the previous solutions, KF and EKF filters are used, which are inefficient in dealing with high nonlinearity systems such as quadcopter. The proposed algorithm is developed by the robust nonlinear filter, Unscented Kalman Filter (UKF), as an angular and linear estimation filter. Simulation results show that the proposed algorithm is efficient to decrease the effect of sensors noise and estimate accurate angular and linear states. Also, improving the stability and performance properties of the quadcopter. In addition, the new algorithm leads to increasing the range of nonlinearity movements that quadcopter can perform it.
This article presents a power-efficient low noise amplifier (LNA) with high gain and low noise figure (NF) dedicated to satellite communications at a frequency of 435 MHz. LNAs’ gain and NF play a significant role in the designs for satellite ground terminals seeking high amplification and maintaining a high signal-to-noise ratio (SNR). The proposed design utilized the transistor (BFP840ESD) to achieve a low NF of 0.459 dB and a high-power gain of 26.149 dB. The study carries out the LNA design procedure, from biasing the transistor, testing its stability at the operation frequency, and finally terminating the appropriate matching networks. In addition to the achieved high gain and low NF, the proposed LNA consumes as low power as only 2 mW.