In radar target tracking application, the observation noise is usually non-Gaussian, which is also referred as glint noise. The performances of conventional trackers degra de severely in the presence of glint noise. A...In radar target tracking application, the observation noise is usually non-Gaussian, which is also referred as glint noise. The performances of conventional trackers degra de severely in the presence of glint noise. An improved particle filter, Markov chain Monte Carlo particle filter (MCMC-PF), is applied to cope with radar target tracking when the measurements are perturbed by glint noise. Tracking performance of the filter is demonstrated in the present of glint noise by computer simulation.展开更多
A new fusion tracking algorithm is presented to track maneuvering target in three-dimensional (3D) space with bearings-only measurements. With the introduction of passive location and interacting multiple model (IMM) ...A new fusion tracking algorithm is presented to track maneuvering target in three-dimensional (3D) space with bearings-only measurements. With the introduction of passive location and interacting multiple model (IMM) algorithm based on multirate model, the high-rate sequence measurements of two sensors are utilized. Simulation results show that the performance of tracking has been improved. The new algorithm removes the barrier of processing high-rate bearings-only measurements.展开更多
In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge di...In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.展开更多
文摘In radar target tracking application, the observation noise is usually non-Gaussian, which is also referred as glint noise. The performances of conventional trackers degra de severely in the presence of glint noise. An improved particle filter, Markov chain Monte Carlo particle filter (MCMC-PF), is applied to cope with radar target tracking when the measurements are perturbed by glint noise. Tracking performance of the filter is demonstrated in the present of glint noise by computer simulation.
文摘A new fusion tracking algorithm is presented to track maneuvering target in three-dimensional (3D) space with bearings-only measurements. With the introduction of passive location and interacting multiple model (IMM) algorithm based on multirate model, the high-rate sequence measurements of two sensors are utilized. Simulation results show that the performance of tracking has been improved. The new algorithm removes the barrier of processing high-rate bearings-only measurements.
文摘In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.