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For highly nonlinear problems, the linear minimum mean-square error (LMMSE) estimation using a nonlinearly converted measurement can outperform the one using the original measurement. For a function space of measurement conversions, every function in the space can be represented as a linear combination of a basis of the space. Then the LMMSE estimator using a vector with its entries forming a basis...
This paper studies and formulates the problem of distributed filtering with a diffusion strategy for state estimation of a dynamic system by using observations from sensors in a network. The sensor-nodes have estimation ability and work in a collaborative manner. The information transmission across the network abides by the diffusion strategy that each node communicates only with its neighbors. First,...
Our newly proposed approach to extended object tracking (EOT) using extension deformation is simple and effective. This approach assumes that the extension of an object is deformed from an ellipsoidal reference extension, which unfortunately restricts its use for complex extensions. To overcome this weakness, this paper proposes that the current object extension be modeled as deformed from the one...
Evaluating the performance of multi-target tracking with respect to tracks rather than unlabeled estimated points is important and challenging. Existing approaches assume exact knowledge of the ground truth. However, this is far from the reality. This paper proposes a method to deal with the case of unknown ground truth by measuring the difference between mock tracks and the assumed targets in the...
For extended-object/group-target tracking (EOT/GTT), the random-matrix approach is appealing. This approach assumes that the measurements are linear in the state and in the noise with its covariance being a random matrix to represent the object extension or the target group. In practice, however, the measurements are nonlinear in the state and noise. This paper proposes a random-matrix approach for...
Performance evaluation of tracking methods includes methods of relative and absolute performance. Absolute tracking performance is the robust end result presented to a user which determines the product solution for real world analysis. However, to achieve robust performance, the tracking method is subject to the sensor data, filtering performance, and associated models, which requires relative performance...
Due to physical laws or mathematical properties the parameters and/or the states of some dynamic systems satisfy certain constraints, and exploitation of such constraints generally is expected to produce more accurate system models. This paper is concerned with modeling of the dynamic systems with equality constraints. An effective framework of the constrained dynamics modeling is proposed by which...
As an important navigation technology, the inertial navigation system (INS) has been widely used in various applications and many INS algorithms have been proposed. Their performance evaluation is crucial for evaluating and improving the algorithms, where the ground truth is assumed known. However, knowledge of the ground truth is hard to acquire, and this presents a challenge to performance evaluation...
This paper presents a new high frequency resolution framework to improve uniformly most powerful (UMP) test based voice activity detection (VAD). The high frequency resolution is employed to make use of the contextual information of neighbor frames. The VAD decision is made by comparing the geometric average of SNR measures to the adaptive threshold which is decided with noise statistics by UMP test...
This paper considers a probabilistic approach to state estimation for discrete-time dynamic systems with unknown inputs. A variational Bayes method is proposed to approximate the marginal posterior distributions of system state and input. In order to reduce the computational complexity, the complete-data likelihoods of system from the exponential family are considered, and the conjugate prior distributions...
The state of some practical dynamic systems satisfies constraints, which can be utilized to improve the performance of state estimation. State estimation with nonlinear inequality constraints is a challenging problem. Projection methods are widely used to solve this problem. In this paper, a projection method is formulated as a special nonlinear function. Based on this formulation, unconstrained estimated...
Although methods for target maneuver onset detection (MOD) abound, few have been proposed for target maneuver termination detection (MTD), since MOD is easier and considered more important. Without MTD, however, decision based maneuvering target tracking is not complete and may suffer from performance degradation and computational waste. This paper proposes sequential testing methods for MTD in the...
This paper presents a requirement ontology which can represent both sentence level semantics which means semantics in the structure of a sentence, and word level semantics which means the meaning of a word. In this way, complete semantics of a sentence can be described. The Generalized Upper Model (GUM) is a widely used linguistically motivated ontology which supplies a hierarchy of general concepts...
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