AlSharif, Mohammed H.; Saad, Mohamed; Siala, Mohamed; Ballal, Tarig; Boujemaa, Hatem; Al-Naffouri, Tareq Y.(2017 25th European Signal Processing Conference (EUSIPCO), Institute of Electrical and Electronics Engineers (IEEE), 2017-11-02)[Conference Paper]
This paper presents a new adaptation of Zadoff-Chu sequences for the purpose of range estimation and movement tracking. The proposed method uses Zadoff-Chu sequences utilizing a wideband ultrasonic signal to estimate the range between two devices with very high accuracy and high update rate. This range estimation method is based on time of flight (TOF) estimation using cyclic cross correlation. The system was experimentally evaluated under different noise levels and multi-user interference scenarios. For a single user, the results show less than 7 mm error for 90% of range estimates in a typical indoor environment. Under the interference from three other users, the 90% error was less than 25 mm. The system provides high estimation update rate allowing accurate tracking of objects moving with high speed.
Alanazi, Abdulrahman; Ballal, Tarig; Masood, Mudassir; Al-Naffouri, Tareq Y.(2017 25th European Signal Processing Conference (EUSIPCO), Institute of Electrical and Electronics Engineers (IEEE), 2017-11-02)[Conference Paper]
The image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solving a regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. This perturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of the regularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularization parameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.
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