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In this paper, we propose a new approach to estimate the low-frequency oscillatory modes in power system by using Total Least Square-Estimation of Signal Parameters employing rotational invariance technique (TLS-ESPRIT) based on Least Mean Squares Sign-Data (LMSSD) Adaptive filtering. LMSSD adaptive filtering reduces the effect of Additive White Gaussian Noise (AWGN) from the signal. The proposed...
This paper proposes a novel estimation method using finite impulse response (FIR) filter for the vehicle roll and bank angles. A vehicle model was constructed using the bicycle model and roll motion model and has parameter uncertainties. The proposed method ensures robust to vehicle parameter uncertainties and has no risk of divergence. Furthermore, the proposed method does not need to use expensive...
In monocular vision systems, lack of knowledge about metric distances caused by the inherent scale ambiguity can be a strong limitation for some applications. We offer a method for fusing inertial measurements with monocular odometry or tracking to estimate metric distances in inertial-monocular systems and to increase the rate of pose estimates. As we performed the fusion in a loosely-coupled manner,...
In this paper, we propose an approach to distributed localization and motion control of unicycle mobile agents for the target circumnavigation problem. The bearing angle measurement-based localization performs when not all the agents get access to the target, but its performance is decided by the motion behaviors, and vice versa. Therefore we propose a coupled framework where we estimate the relative...
In this paper we present a novel approach for depth map enhancement from an RGB-D video sequence. The basic idea is to exploit the photometric information in the color sequence. Instead of making any assumption about surface albedo or controlled object motion and lighting, we use the lighting variations introduced by casual object movement. We are effectively calculating photometric stereo from a...
We study the problem of single-image depth estimation for images in the wild. We collect human annotated surface normals and use them to help train a neural network that directly predicts pixel-wise depth. We propose two novel loss functions for training with surface normal annotations. Experiments on NYU Depth, KITTI, and our own dataset demonstrate that our approach can significantly improve the...
This paper provides an experimental result of non-contact vital sensing by a Doppler sensor for multiple targets. This is based on the signal processing scheme that is termed as differential of accumulation for real-time serial-to-parallel converter (DARS). To the best of authors' knowledge, there is no extant studies dealing with multiple targets with a Doppler sensor. In this experiment, we employ...
Inductor current in the high speed switching converters is used as a feedback signal for current mode control and over current fault protection. Sensing inductor current for the use of digital controllers require high bandwidth current sensors and also need high speed Analog to Digital Converter (ADC) to convert the sensed current into digital domain. Use of high bandwidth current sensors and high...
In Internet of Things (IoT) world, there can be many sensors deployed in a system, thus their costs must be considered during the system design and material selections, in order to support massive production and deployment. Design-To-Cost (DTC) is an effective technique for this situation. In Model-Based Design (MBD), DTC cost estimates are preferred to be generated from models as one of the parameters...
The need to improve the quality of management at minimum costs, the complexity of the structure of the management object, the functions performed by it, leads to an increase in uncertainties that need to be taken into account.
A method is proposed for estimation of occluded space and generation of auxiliary points for 3D position estimation of strongly occluded objects. First, occlusion space detection calculates 3D keypoints at the rear side of a target object, thus obtaining a silhouette around the object on the near side, as found from a camera image by an object detector. The method calculates the space containing the...
Accurate estimation of the vehicle sideslip angle is fundamental in vehicle dynamics control and stability. In this paper two different methods for vehicle sideslip estimation, based on Principal Component Analysis (PCA) and Neural Networks (NN), are presented comparing the procedure responses with full-scale vehicle acquired test data. The estimation algorithms use driver's steering angle, lateral...
Nutrition is an important factor in the prevention and treatment of many diseases. Nutrition is a key factor for obesity, which is a risk factor for cardio-vascular diseases, type-2 diabetes and even cancer. Many non-communicable diseases require patients to keep track of nutrition accurately. Diabetes type-2 and type-1 require tracking carbohydrate intake accurately. However, keeping track and even...
State-of-the-art sensing methods only exploit three dimensions of the spectrum space: frequency, time and geography whereas the angle dimension, that is, spatial spectrum sensing has not been exploited well enough. In this paper, we apply the multiple signal classification (MUSIC) Angle of Arrival (AoA) estimation method into spectrum sensing. Note that MUSIC method needs to know the number of signals,...
A vast majority of consumer cameras operate the rolling shutter mechanism, which often produces distorted images due to inter-row delay while capturing an image. Recent methods for monocular rolling shutter compensation utilize blur kernel, straightness of line segments, as well as angle and length preservation. However, they do not incorporate scene geometry explicitly for rolling shutter correction,...
With the development of unmanned aerial vehicles (UAVs) and the relevant techniques, UAVs become common and popular for civilian applications such as remote sensing tasks. The reason is because they are cheap, flexible, and easy to set up. Car park occupancy analysis is important for authorities to make decisions on the design, plan and management of car parks. To have a quick knowledge of current...
In this paper, driver intention estimation near a road intersection is presented, using discrete hidden Markov models (HMM) and the Hybrid State System (HSS) framework as basis. The development of Advanced Driver Assistance Systems (ADAS) has assisted drivers in many driving scenarios and resulted in safe driving. Developing techniques to estimate driver's intention leads to the advancement of ADAS...
We demonstrate a novel technique for distributed Brillouin frequency estimation by fitting the Brillouin transfer function directly in the complex domain. Experimental results show the uncertainty of Brillouin frequency can be significantly reduced compared with the approaches based solely on Brillouin gain or phase.
In this paper, we propose and analyze new spectrum-efficient communication and radar sensing systems (named ComSens) operating in full-duplex mode with frequency division duplex scheme. ComSens simultaneously use the pilot overhead for channel estimation and radar sensing. The performances of ComSens are analyzed in terms of ergodic communication data-rate and radar estimation rate. The total system...
This paper studies a selection of estimation schemes for tracking problems where sensors measure range and Doppler while no directional measurements are provided. The selected estimators are relatives of the Kalman filter where either the state propagation equation or the measurement equation is non-linear. Known schemes are compared with a new filter operating in Cartesian state space. The new filter...
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