Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Conference Object Approximate Best Linear Unbiased Channel Estimation for Multi-Antenna Frequency Selective Channels With Applications To Digital Tv Systems(SPIE, 2004) Özen, Serdar; Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark J.; Zoltowski, Michael D.We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication receivers with multiple-antenna. Our algorithm is best suited for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols, and the receivers for this particular system are expected work in a severe frequency selective multipath environment with long delay spreads relative to the length of the training sequence. The iterative procedure calculates the (semi-blind) Best Linear Unbiased Estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, denoted by a-BLUE, achieving almost similar performance, with much lower complexity. Indeed we show that, with reasonable assumptions, a-BLUE channel estimate can be obtained by using a stored copy of a pre-computed matrix in the receiver which enables the use of the initial CIR estimate by the subsequent equalizer tap weight calculator. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC Digital TV system. We also provide a simulation study of the robustness of the a-BLUE algorithm to timing and carrier phase offsets.Article Citation - WoS: 1Citation - Scopus: 3Euclidean Position Estimation of Static Features Using a Moving Uncalibrated Camera(Institute of Electrical and Electronics Engineers Inc., 2012) Nath, Nitendra; Dawson, Darren M.; Tatlıcıoğlu, EnverIn this paper, a novel Euclidean position estimation technique using a single uncalibrated camera mounted on amoving platform is developed to asymptotically recover the 3-D Euclidean position of static object features. The position of the moving platform is assumed to be measurable, and a second object with known 3-D Euclidean coordinates relative to theworld frame is considered to be available a priori. To account for the unknown camera calibration parameters and to estimate the unknown 3-D Euclidean coordinates, an adaptive least squares estimation strategy is employed based on prediction error formulations and a Lyapunovtype stability analysis. The developed estimator is shown to recover the 3-D Euclidean position of the unknown object features despite the lack of knowledge of the camera calibration parameters. Numerical simulation results along with experimental results are presented to illustrate the effectiveness of the proposed algorithm. © 2011 IEEE.Conference Object Citation - Scopus: 1Euclidean Position Estimation of Static Features Using a Moving Uncalibrated Camera(Institute of Electrical and Electronics Engineers Inc., 2009) Nath, Nitendra; Dawson, Darren M.; Tatlıcıoğlu, EnverIn this paper, a novel Euclidean position estimation technique using a single uncalibrated camera mounted on a moving platform is developed to asymptotically recover the three-dimensional (3D) Euclidean position of static object features. The position of the moving platform is assumed to be measurable, and a second object with known 3D Euclidean coordinates relative to the world frame is considered to be available a priori. To account for the unknown camera calibration parameters and to estimate the unknown 3D Euclidean coordinates, an adaptive least squares estimation strategy is employed based on prediction error formulations and a Lyapunov-type stability analysis. The developed estimator is proven to recover the 3D Euclidean position of the unknown object features despite the lack of knowledge of the camera calibration parameters.