This paper presents an all-parametric model of radar target in optic region, in which the localized scattering center's frequency and aspect angle dependent scattering level, distance and azimuth locations are mod...This paper presents an all-parametric model of radar target in optic region, in which the localized scattering center's frequency and aspect angle dependent scattering level, distance and azimuth locations are modeled as the feature vectors. And the traditional TLS-Prony algorithm is modified to extract these feature vectors. The analysis of Cramer-Rao bound shows that the modified algorithm not only improves the restriction of high signal-to-noise ratio(SNR)threshold of traditional TLS-Prony algorithm, but also is suitable to the extraction of big damped coefficients and high-resolution estimation of near separation poles. Finally, an illustrative example is presented to verify its practicability in the applications. The experimental results show that the method developed can not only recognize two airplane-like targets with similar shape at low SNR, but also compress the original radar data with high fidelity.展开更多
This paper gives a theorem for the local center of generalized Lienard system; the relative theorems in the references can be deduced from our corollaries.
The novel eye-based human-computer interaction(HCI) system aims to provide people, especially, disabled persons,a new way of communication with surroundings. It adopts a series of continual eye movements as input to p...The novel eye-based human-computer interaction(HCI) system aims to provide people, especially, disabled persons,a new way of communication with surroundings. It adopts a series of continual eye movements as input to perform simple control activities. Identification of eye movements is the crucial technology in these eye-based HCI systems. At present, researches on eye movement identification mainly focus on frontal face images. In fact, acquisition of non-frontal face images is more reasonable in real applications. In this paper, we discuss the identification process of eye movements from non-frontal face images. Firstly, the original head-shoulder images of 0?–±60?azimuths are sampled without any auxiliary light source. Secondly, the non-frontal face region is detected by using the Adaboost cascade classifiers. After that, we roughly extract eye windows by the integral projection function.Then, we propose a new method to calculate the x- y coordinates of the pupil center point by searching the minimal intensity value in the eye windows. According to the trajectory of the pupil center points, different eye movements(eye moving left, right, up or down)are successfully identified. A set of experiments is presented.展开更多
文摘This paper presents an all-parametric model of radar target in optic region, in which the localized scattering center's frequency and aspect angle dependent scattering level, distance and azimuth locations are modeled as the feature vectors. And the traditional TLS-Prony algorithm is modified to extract these feature vectors. The analysis of Cramer-Rao bound shows that the modified algorithm not only improves the restriction of high signal-to-noise ratio(SNR)threshold of traditional TLS-Prony algorithm, but also is suitable to the extraction of big damped coefficients and high-resolution estimation of near separation poles. Finally, an illustrative example is presented to verify its practicability in the applications. The experimental results show that the method developed can not only recognize two airplane-like targets with similar shape at low SNR, but also compress the original radar data with high fidelity.
文摘This paper gives a theorem for the local center of generalized Lienard system; the relative theorems in the references can be deduced from our corollaries.
基金supported by Innovation Program of Shanghai Municipal Education Commission of China(No.14YZ169)
文摘The novel eye-based human-computer interaction(HCI) system aims to provide people, especially, disabled persons,a new way of communication with surroundings. It adopts a series of continual eye movements as input to perform simple control activities. Identification of eye movements is the crucial technology in these eye-based HCI systems. At present, researches on eye movement identification mainly focus on frontal face images. In fact, acquisition of non-frontal face images is more reasonable in real applications. In this paper, we discuss the identification process of eye movements from non-frontal face images. Firstly, the original head-shoulder images of 0?–±60?azimuths are sampled without any auxiliary light source. Secondly, the non-frontal face region is detected by using the Adaboost cascade classifiers. After that, we roughly extract eye windows by the integral projection function.Then, we propose a new method to calculate the x- y coordinates of the pupil center point by searching the minimal intensity value in the eye windows. According to the trajectory of the pupil center points, different eye movements(eye moving left, right, up or down)are successfully identified. A set of experiments is presented.
