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We present an autonomous quadrotor system that is able to perform high precision landing on small platform in both indoor and outdoor environment. Its taking off and landing processes are fully autonomous. We use vision sensor to detect the landing platform, and the vision measurement is enhanced by IMU with SRUKF based sensor fusion method. All computation are done real-time and on-board. We implement...
Automatic robot / Computed Tomography (CT) scanner registration is an important feature for robot-assisted percutaneous needle placement under CT-scanner. This registration can be done using 3D images, but for fast, low X-ray radiation it is interesting to be able to perform the registration with a single slice. In this paper, a new marker is proposed, which allows to estimate the pose of a device...
The traditional MUSIC algorithm for MIMO radar angle estimation has been improved to reduce the amount of arithmetic operations. The N-th power of the inverse matrix is applied to approximate the noise subspace to eliminate the requirement of distinguishing the signal and the noise subspace. The combination of the eigenvalues and eigenvectors replaces the N-th power of the inverse covariance matrix...
This paper studies the consensus of multi-agent systems with binary-valued communication. We consider a group of agents on an undirected graph with a fixed topology, but differing from most existing work, each agent cannot get the true value of its neighbors' states. What information each agent gets from its neighbors is binary-valued measurement. A two-scale control algorithm is constructed: Each...
Many techniques, such as parameter extraction techniques are used in ultrasonic signal processing. In this paper, the matching pursuit decomposition (MP) and differential evolution (DE) have been tested for parameters estimation, denoising and compression of ultrasonic echoes. The method is based on the MP algorithm who does the decomposition of the ultrasonic signal into elementary functions (atoms)...
Adaptive software systems are designed to cope with unpredictable and evolving usage behaviors and environmental conditions. For these systems reasoning mechanisms are needed to drive evolution, which are usually based on models capturing relevant aspects of the running software. The continuous update of these models in evolving environments requires efficient learning procedures, having low overhead...
In general, an image degraded by blurring or defocusing is restored by deconvolution using a substantially constant PSF. However, in the case of a confocal laser microscope, there is a problem that the PSF varies according to the depth of focus. In order to overcome this problem, we adopt the iterative approach to estimate the PSF by a blind deconvolution. In order to confirm the effectiveness of...
It has always been difficult to accurately estimate the moment of inertia of an object, e.g. an unmanned aerial vehicle (UAV). Whilst various offline estimation methods exist to allow accurate parametric estimation by minimizing an error cost function, they require large memory consumption, high computational effort, and a long convergence time. The initial estimate's accuracy is also vital in attaining...
The problem of identification of autoregressive (AR) signals with noisy measurements is considered. A new algorithm is proposed to estimate the AR parameters. To cope with the effect of the measurement noise that causes a bias in the least-squares estimate of the AR parameters, an efficient procedure is developed for estimating the measurement noise variance. The proposed identification algorithm...
Current concerns about data privacy have lead to increased focus on data anonymization methods. Differential privacy is a new mechanism that offers formal guarantees about anonymization strength. The main challenge when using differential privacy consists in the difficulty in designing correct algorithms when operating on complex data types. One such data type is sequential data, which is used to...
The aim of the SONIC project is to develop tools to investigate and mitigate the effects of underwater noise generated by shipping. One way to study the contribution of shipping noise to the background noise in the seas is to produce shipping noise maps. The SONIC project delivers the required technical knowledge for noise mapping, based on a source definition of shipping traffic composed of various...
In this paper, we propose a test of hypothesis improvement, by phase study of the analytical cross-correlation function in acoustical detection application. Robustness of false alarms probability for the Time Of Arrival (TOA) estimation represents the goal of the proposed method. After signal detection, TOA will be used to localize one receiver, thanks to a grid of transmitters (more than 3), thanks...
This study presents an innovative way for underwater acoustic signal analysis. It is based on multi-directional filters implementation on time-frequency representation, where each filter is designed to enhance a given direction on the time-frequency plane. To do so, the proposed technique processes the time-frequency plane by taking into account the actual atom and its neighborhood for each direction,...
Calibration models have been widely used for estimating product quality or other key variables with near-infrared spectroscopy (NIRS), and it is important to select appropriate input variables (wavelengths) for building a highly accurate calibration model. A novel input variable selection method based on nearest correlation spectral clustering (NCSC), which is a correlation-based clustering method,...
In an asteroid exploration and sample return mission, accurate estimation of the shape and motion of the target asteroid is essential for selecting a touchdown site and navigating a spacecraft during touchdown operation. In this work, we present an automatic estimation method for the shape and motion of an asteroid, which is planned to be tested in future exploration missions including Japanese Hayabusa-2...
This paper focuses on application of a particle filter for online identification of non-Gaussian systems. Firstly, the Bayesian inference was described and then the particle filter was defined. The particle filter numerically solves a problem of a recursive Bayesian state estimator. Secondly, the parameters of the linear system and two types of the non-Gaussian systems were estimated by application...
In this paper, we develop a Bayesian short-time spectral amplitude (STSA) estimator with the purpose of singlechannel speech enhancement in the presence of moderate levels of non-stationary noise. In this regard, we first apply a minimum mean squared error (MMSE) approach for the joint estimation of the short-term predictor (STP) parameters of the speech and noise signals, from the noisy speech observations...
We investigate cooperative in-band radar and communications signaling for frequency-modulated continuous-wave (FMCW) radar and Doppler estimation. While each system typically considers the other system a source of interference, by considering the radar and communications operations to be a single system, joint performance bounds can be formulated. We extend previous work where a novel estimation and...
The performances of sixteen equation error methods for continuous-time system identification are compared through a simulation example with the CONTSID toolbox. The influence of the sampling period, the type of input signal (piece-wise constant or band-limited) and the noise (level and type: white/colored) is studied. The methods are then classed according to quantitative and qualitative criteria.
The problem of source separation in two dimensions is studied in this paper. The problem is formulated in the Bayesian framework. The sources are modelled as MRFs to accommodate for the spatially correlated structure of the sources, which we exploit for separation in 2D. The difficulty of working analytically with general Gibbs distributions is overcome by using an approximate density. In this work,...
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