May 2013 Issue Vol.3 No.5

At 900 MHz carrier frequency equalizing the Doppler effect in M-QAM at 18dB gain

Sanjeev Kumar Shah #1, Vinay Negi #2, Sandeep Singh #3
# Electronics and communication, Uttaranchal Institute Of Technology, Dehradun, Uttarakhand, India

Abstract: This paper describes the calculation and simulation results of the Doppler effect on a mobile car with the help of constellation diagram for 4 QAM modulation when the mobile car experienced the Rayleigh fading. And the equalizer is used to optimize the Doppler effect. Here LMS Linear equalizer is used to optimize the Doppler effect when the Mobile Car having speed 30 m/sec. and the mobile car is assumed on freeway. The results are taken at three position of mobile car i.e. at an angle of 50,450 and 850.
Keywords: 4 QAM modulation, LMS Linear equalizer, Rayleigh fading, Doppler effect, constellation diagram.

GPS – IMU based Autonomous Target Tracking Algorithm for use in UAS

JaganathanRanganathana and William H. Semkeb a University of North Dakota, Department of Earth System Science & Policy Clifford Hall Room 333, 4149 University Ave Stop 9011, Grand Forks, ND 58202, USA b University of North Dakota, Department of Mechanical Engineering Upson II Room 271, 243 Centennial Drive Stop 8359, Grand Forks, ND 58202, USA

Abstract: Tracking a ground based target autonomously from an Unmanned Aircraft Systems (UAS) is a critical task for remote sensing or any Intelligence, Surveillance, and Reconnaissance (ISR) mission that requires precision pointing, and effective real-time data transmission/recording to the ground station. To achieve this, the authors introduce a novel non-linear closed form analytical algorithm derived based on coordinate transformation and vector algebra principles that was implemented onboard a small UAS. The Unmanned Aircraft Systems Engineering Laboratory (UASE) at University of North Dakota (UND), Grand Forks, ND developed a small UAV payload “SUNDOG” to demonstrate the autonomous tracking ability of the derived algorithm and its implementations. The major advantage of the algorithm is that, it allows the user to specify and maintains the camera/target orientation irrespective of the aircraft position and rotation, which helps the ground personnel to easily interpret the data effectively while tracking the target location in real-time. The equations provide an elegant closed form solution to a non-linear problem that can be easily and efficiently programmed. The algorithm was verified through several experimentations and demonstrated successfully in an UAS test flight. Actual flight data illustrating the effectiveness of the surveillance algorithm is presented.

Keywords: Autonomous Tracking Algorithm, Precision Pointing, Multi-Axis Gimbal Tracking, Mini-UAV Payload

Read complete May 2013