مقالههای M. A. MASNADI
توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقالههای نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده میشوند.
اطلاعات انتشار: Volume ۴. Number ۲ - July / December ۲۰۰۶، سال ۰
تعداد صفحات: ۱۴
اطلاعات انتشار: Iranian Journal of Science and Technology Transactions of Electrical Engineering، سي و ششم،شماره۲، ۲۰۱۲، سال ۰
تعداد صفحات: ۱۴
Most previous studies in estimation of the target position and velocity through Bearing Only Measurements (BOM) consider targets with constant velocity moving along a straight line. In this paper, state and measurement equations are presented for moving targets with constant acceleration by using the previously presented state vector in the Extended Modified Polar Coordinates (EMPC) system. In the BOM systems, by increasing the distance between target and observer (Own ship) the estimation accuracy of the target kinematic parameters degrades noticeably. In order to solve this problem, here the idea of hybrid data measurements is presented. In this approach both low rate range information, from active sensor, and high rate BOM are exploited. The improvement in the performance of the hybrid system compared to BOM system is represented through computer simulations.
اطلاعات انتشار: Iranian Journal of Science and Technology Transactions of Electrical Engineering، سي و نهم،شماره۱، ۲۰۱۵، سال ۰
تعداد صفحات: ۲۱
In this paper the problem of minimizing the total transmitting power subject to a fixed total bit rate in OFDM systems is considered. Upper bounds on transmitting power and bit rate of each subcarrier can also be taken into account. In practice, the number of bits of each subcarrier should be integer and nonnegative. In this paper an analytical optimal solution is derived for the case of assuming the bits to be integer. Then, the solution is extended for the case of nonnegative integer bits and the cases in which we have constraints on the maximum power and bit rate of each subcarrier. In an OFDM system with N subcarriers the complexity of computing the proposed analytical solution is O(N) which is lower than the computational complexity of existing algorithms. In addition to the mathematical proofs, computer simulations confirm that the proposed analytical solution is optimal and faster than the existing algorithms.
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