Browsing by Author "WU, WR"

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A NONLINEAR IMM ALGORITHM FOR MANEUVERING TARGET TRACKING
(1994-07-01)
WU, WR
;
CHENG, PP
;
交大名義發表
;
電信工程研究所
;
National Chiao Tung University
In target tracking, the measurement noise is usually assumed to be Gaussian. However, the Gaussian modeling of the noise may not be true. Noise can be non-Gaussian. The non-Gaussian noise arising in a radar system is known as glint noise. The distribution of glint noise is long tailed and will seriously affect the tracking performance. We develop a new algorithm that can effectively track a maneuvering target in the glint environment. The algorithm incorporates the nonlinear Masreliez filter into the interactive multiple model (IMM) method. Simulations demonstrate the superiority of the new algorithm.
IMAGE ESTIMATION USING FAST MODIFIED REDUCED UPDATE KALMAN FILTER
(1992-04-01)
WU, WR
;
KUNDU, A
;
電信工程研究所
;
Institute of Communications Engineering
In this paper, we have proposed some modifications of the reduced update Kalman filter (RUKF) as applied to filtering of images corrupted by additive noise. First, we have reduced the computational complexity by reducing the state dimensionality. By doing so, it is shown in the paper that the computational requirement is reduced by an order of magnitude while the loss of performance is only marginal. Next, the RUKF is modified using the score function based approach to accommodate the non-Gaussian noise. The image is modeled as a nonstationary mean and stationary variance autoregressive Gaussian process. It is shown in the paper that the stationary variance assumption is reasonable if the nonstationary mean is computed by an edge and detail preserving efficient estimator of local nonstationary mean. Such an estimator called HMSMD filter is also described in the paper. Finally, detailed experimental results are provided which indicate the success of the new filtering scheme.
TARGET TRACKING WITH GLINT NOISE
(1993-01-01)
WU, WR
;
交大名義發表
;
National Chiao Tung University
In tracking targets, there can be an uncertainty associated with the measurements in addition to their inaccuracy, which is usually modeled by additive Gaussian noise. However, the Gaussian modeling of the noise may not be true. Noise can be non-Gaussian. The non-Gaussian noise arising in a radar system is known as glint noise. The distribution of glint noise is long tailed and will seriously affect the tracking performance. A new algorithm is developed here which can significantly improve the tracking performance when the glint noise is present.
THEORETIC ANALYSIS OF THE gamma-LMS ALGORITHM
(1994)
WU, WR
;
CHEN, PC
;
電信工程研究所
;
Institute of Communications Engineering
WEIGHTED D-FILTERING
(1991-04-01)
WU, WR
;
KUNDU, AL
;
友訊交大聯合研發中心
;
D Link NCTU Joint Res Ctr
In this paper, we have proposed a new type of filter which has the most desirable properties of an image smoothing filter. These properties are 1) robust smoothing efficiency, 2) edge preservation, and 3) thin-line detail preservation. The new filter computes its output as the median of weighted averages, instead of plain averages as used in the Hodges-Lehman D-filter, of symmetrically placed order statistics. One particular weighting scheme is considered in details for experiments. The experimental and comparison results are included verifying the useful properties of the proposed filter.