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We present a particle filter for multi-object tracking that is based on the ideas of the Approximate Bayesian Computation (ABC) paradigm. The main idea is to avoid the explicit computation of the likelihood function by means of simulation. For this purpose, a large amount of particles in the state space is simulated from the prior, transformed into measurement space, and then compared to the real...
In this paper, a novel quaternion adaptive filtering algorithm is proposed for a unified processing of 3D and 4D data, called quaternion least mean kurtosis (QLMK) algorithm. Multi-dimensional signals exhibit a complex nonlinear relationship and couple among different components. Considering that quaternion has huge advantage in terms of the representation of 3D and 4D signal, quaternion algebra is...
With the development of deep space exploration, the requirements of accuracy and real time for navigation services become higher, so that the traditional ground based network can hardly meet the user's needs. And the accuracy of existing autonomous navigation method, such as celestial navigation, cannot meet the requirement either. In order to improve the performance of autonomous navigation for deep...
This paper presents a novel and an improved approach for estimating the position of a vehicle using vehicle-infrastructure cooperative localization. In our previous work we presented a Factor Graph based solution which added the topology (inter-vehicle distance) as a constraint while localizing the vehicle using data from sensors from both inside and outside the vehicle. This paper extends the work...
In this paper, a new centralized algorithm is developed to estimate the registration error and target states jointly based on the generalized labeled multi-Bernoulli (GLMB) filter. The bias pseudo-measurements are calculated with the tracks generated by the GLMB filter. Then, the bias estimates are computed to compensate the measurements for multi-target tracking. Since the estimates of the sensor...
The Fisher information matrix is applied to evaluate the performance of three different navigation methods for the constellation around the libration points. Where the X-ray pulsar relative navigation is the main method, and the starlight Doppler relative navigation and the intersatellite links are integrated with it respectively. Their measurement quantities are respectively the time difference of...
This paper explores a novel model to describe linear dynamic system with random delays. Compared with the existing research, the probabilities of random delays in the novel model are calculated by conditional probabilities. Therefore, the process noises and measurements noises in the new model for random delay problems are infinitely correlated. By treating the model as random parameter matrices Kalman...
An autonomous navigation scheme for unmanned aerial vehicles is presented based on visual and inertial measurement information fusion without the known ground cooperative target. The UAV relative translation and rotation motion parameters are estimated by inter-frame image feature detection and tracking. Then the relative motion parameters are considered to be the relative pose measurements of two...
Bayesian filters are often used in statistical inference and consist of recursively alternating between two steps: prediction and correction. Most commonly the Gaussian distribution is used within the Bayes filtering framework, but other distributions, which could model better the nature of the estimated phenomenon like the von Mises-Fisher distribution on the unit sphere, have also been subject of...
Big classes of directional distribution laws generalizing the von Mises distribution are provided in [4] following a general geometric offset approach in [20]. Once a distribution law is estimated for modeling a given data set, one of the next steps of statistical analysis is simulating from such distribution. The von Mises distribution was simulated in [1] using an acceptance-rejection simulation...
Pulsars autonomous navigation is characterized by its credible performance and high navigation accuracy, which will have broad prospects for use in deep-space autonomous navigation. In our study, we find the observation time required for different pulsars to obtain the same time of arrival (TOA) accuracy is different, which means the rates of different sensors are different. However, the previous...
The ball state tracking and detection technology plays a significant role in volleyball game analysis for volleyball team supporting and tactics development. This paper proposes a ball event detection method to achieve high detection rate by solving challenges including: the great variety of event length, the large intra-class difference of one event and the influence caused by ball trajectories....
In this paper, we report on a body state and ground profile estimator for a snake-like robot executing a rolling gait to travel from flat ground to a slope. With the help of the estimator, the snake-like robot can adaptively adjust the body shape and locomotion speed by changing the gait parameters for the purpose of tackling a steep slope. Specifically, we propose a repeating sequence of continuous...
A real-time multi-mode robust filtering method is proposed for the large thrust and slow spin characteristics of the rocket above the flight stage. The rocket upper stage in the sliding section of the existence of slow spin characteristics, which will lead to ground measurement equipment tracking instability, poor measurement data quality. In order to solve this problem, the robustness theory and...
Tracking hypersonic glide reentry vehicles (HGRVs) is considered in the paper. Firstly, justified by an analysis of dynamic models of HGRVs, we proposed a more accurate motion model with less computation burden. Secondly, fixed-interval Gaussian mixture approximation smoother for non-linear Markov jump systems (NLMJSs) is presented in the paper. The Gaussian mixture filter can effectively approximate...
We develop an Expectation-Maximization (EM) algorithm for the simultaneous tracking and shape estimation of a star-convex object based on multiple spatially distributed measurements. In order to formulate the problem within the EM framework, the unknown measurement sources on the object are modeled as hidden variables. As the measurement sources are continuous quantities, we develop a suitable discretization...
Conventional point object model based automotive radar tracking system assumes at most one detection received from the target object at a time. However, in real applications for an extended object, such as a passenger car, located within a close range to a high-resolution radar or LIDAR, the system usually receives multiple reflections from different parts of the object. This can introduce large bias...
The Gaussian inverse Wishart (GIW) filter is a promising filter for extended target tracking and draws tremendous attention in recent years. The Gaussian and the inverse Wishart distributions are used to describe the target's kinematical and extended states, respectively. However, the filter for estimating the extended state contains predicting position error and causes large error of the extended...
Data from three-way measurement is a kind of important observing data for deep space probes. By utilizing this data, this paper presents an algorithm to calculate the real-time position of deep space probes based on UKF (unscented Kalman Filter). The observing model and forecast method using the three-way measurement are given with the implementation method via dynamic modeling and non-dynamic modeling...
Several estimation algorithms have been developed in the literature to improve the radar tracking performance of ballistic targets. The most widely used one of these algorithms is the Extended Kalman Filter (EKF) where nonlinear system and measurement models and linearization techniques are used. In the first method presented in this paper, the kinematic state vector composed of the position and velocity...
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