This paper proposes a modified detection scheme which reduces the performance gap between the V-BLAST MMSE detection algorithm and the maximum likelihood (ML) detection. In V-BLAST detection algorithm error propagatio...
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This paper proposes a modified detection scheme which reduces the performance gap between the V-BLAST MMSE detection algorithm and the maximum likelihood (ML) detection. In V-BLAST detection algorithm error propagation due to unreliable decision feedback severely limits the system performance. Here, we propose a new detection scheme that reduces the destructive effect of error propagation to a great extent. In our proposed detection algorithm, we have used ML detection to jointly estimate two strongest sub-streams of the transmitted data. For this purpose, we find an optimum beam-forming matrix to minimize the power of cumulative noise and the interfering sub-streams. It is shown that the proposed scheme outperforms the conventional V-BLAST MMSE algorithm with moderate increase in computational complexity. Nevertheless, our study shows that the complexity of our proposed algorithm is almost negligible compared to maximum likelihood detection.
The objective of this paper is to develop novel classification structures for military targets detection and recognition by employing different fusion techniques. In real applications, the great diversity of materials...
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The objective of this paper is to develop novel classification structures for military targets detection and recognition by employing different fusion techniques. In real applications, the great diversity of materials in the background areas and the similarity between the background and target signatures result in high false alarm rates and large miss classification errors. In this paper, two novel target detection and recognition systems are proposed using different fusion techniques: decision fusion and classification fusion employing confidence vectors. These new systems are tested using an experimental data set to assess their effectiveness.
Image segmentation is an essential step in extracting information from raw images for interpretation. Although many segmentation algorithms have been proposed in the literature, image segmentation is still an elusive ...
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Image segmentation is an essential step in extracting information from raw images for interpretation. Although many segmentation algorithms have been proposed in the literature, image segmentation is still an elusive goal in image processing. In this study, we compared and tested four different segmentation techniques for improvement on auroral image segmentation. To extract some useful information from auroral images, Gabor wavelet transform was used to perform the transformations.
This tutorial presents a state-of-the-art survey of advanced applications of Synthetic Aperture Radar (SAR). Applications include: the detection and recognition of targets in SAR imagery, and the detection of targets ...
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This tutorial presents a state-of-the-art survey of advanced applications of Synthetic Aperture Radar (SAR). Applications include: the detection and recognition of targets in SAR imagery, and the detection of targets under trees (and in the open) using change detection (coherent change detection, full-polarization change detection, etc). A fully polarimetric SAR sensor is described. Models of clutter and targets are developed from analysis of full-polarization SAR imagery. algorithms for optimum (GLRT) processing of full-polarization data are derived, including the polarimetric whitening filter (PWF) and the polarimetric matched filter (PMF). Polarization-based discrimination features (polarization entropy, anisotropy, etc.) are developed and applied to SAR image terrain classification. Model-based and template-based target recognition systems are described and classifier performance results versus resolution and polarization are summarized for 10-and 20-target classifiers. Super-resolution algorithms are applied to SAR imagery and target recognition performance improvements demonstrated. Multi-polarization and multi-pass change detection algorithms are developed and demonstrated using UHF SAR imagery of targets under trees; fusion of multi-polarization coherent and non-coherent change detection algorithms is demonstrated. The effect of SAR image compression on change detection performance is quantified. Change detection performance using multi-pass VHF SAR imagery of targets under trees is demonstrated using data gathered by the Swedish CARABAS SAR system.
Quickest detection is applied to frequency spectrum sensing in cognitive radio systems. Distribution change in frequency domain is detected for vacating secondary radio networks from licensed frequency band. A success...
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Quickest detection is applied to frequency spectrum sensing in cognitive radio systems. Distribution change in frequency domain is detected for vacating secondary radio networks from licensed frequency band. A successive refinement based quickest detection is proposed to tackle the problem of unknown parameters of primary radio signal. Cooperative quickest detection is used to enhance the performance of quickest spectrum sensing in secondary radio systems without data fusion centers. Performance is evaluated using theoretical analysis and numerical simulations.
IP1 is a prototype CASA radar sensor network located in southwestern Oklahoma whose goal is to detect severe weather in the lower part of the atmosphere. At the center of this system's control loop is its Meteorol...
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IP1 is a prototype CASA radar sensor network located in southwestern Oklahoma whose goal is to detect severe weather in the lower part of the atmosphere. At the center of this system's control loop is its Meteorological Command and Control (MC&C). In this paper, we presented the overall control architecture for the IP1 network and highlight new features that have recently been added to the MC&C. We also present an analysis of the MC&C performance based on measurement data from a 5-day operation period. In addition, we introduce a distributed version of the MC&C.
In this paper, a fast intra mode decision algorithm based on transform-domain property is proposed to reduce the coding complexity in H.264/AVC encoder. According to the basis patterns for DCT transformation, the 4 ti...
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In this paper, a fast intra mode decision algorithm based on transform-domain property is proposed to reduce the coding complexity in H.264/AVC encoder. According to the basis patterns for DCT transformation, the 4 times 4 block is first transformed and then the transformed coefficients are utilized to detect the tendency of target block. In comparison to the previous fast mode decision algorithms, which measure the edge direction by complex arithmetic operations, the proposed algorithm simplifies the procedure of detection method. Experimental results show that the proposed algorithm can support more accurate prediction in the least bit-rate increment, which outperforms the intra coding time approximately by 55% of the full search method.
Single carrier frequency division multiple access (SC-FDMA) is adopted as uplink multiple access scheme in 3G long-term evolution (LTE). Combining SC-FDMA with MIMO (multiple-input multiple-output) can increase capaci...
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Single carrier frequency division multiple access (SC-FDMA) is adopted as uplink multiple access scheme in 3G long-term evolution (LTE). Combining SC-FDMA with MIMO (multiple-input multiple-output) can increase capacity and throughput but detection technique is required at the base station (BS). Interference cancellation (IC) based on cyclic redundancy check (CRC) is a conventional detection algorithm. In this paper, we divide IC into useful IC and useless IC. Simulation results indicate that CRC-based IC algorithm performs too many useless ICs, which increases the complexity. Thresholded IC algorithm is proposed to reduce the complexity. In the proposed algorithm, IC is performed only when the probability that the IC is useful exceeds a threshold. We select 0.5 as the threshold. With the threshold, the proposed algorithm reduces the complexity significantly and keeps the performance loss negligible.
In this paper, we investigate soft interference cancellation algorithms for vertical Bell Laboratories layered space- time (V-BLAST) systems. By using Gaussian-forcing technique and fast matrix computation, we first d...
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In this paper, we investigate soft interference cancellation algorithms for vertical Bell Laboratories layered space- time (V-BLAST) systems. By using Gaussian-forcing technique and fast matrix computation, we first derive a simplified version of the conventional generalized probabilistic data association (GPDA) algorithm, called the fast soft interference cancellation (FSIC) algorithm, whose complexity is only cubic in the number of transmit/receive antennas. Then, based on the FSIC algorithm, we develop an enhanced soft interference cancellation (ESIC) algorithm by making use of the properties of MIMO channels. It is shown that with efficient iterative processing, the ESIC algorithm can achieve near-optimal performance in both uncoded systems and coded systems.
The fast feature extraction of point cloud data becomes one core of the reverse-engineering CAD modeling researches that are based on point cloud. In the two-dimensional or three-dimensional product contour, the circl...
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The fast feature extraction of point cloud data becomes one core of the reverse-engineering CAD modeling researches that are based on point cloud. In the two-dimensional or three-dimensional product contour, the circle is a very common shape. This paper proposed a new circle extraction method of three-dimensional point cloud data, which is based on the image. This method takes full advantage of the point cloud features and the image, as well as the ellipse detection algorithm of image, for extracting the circle from the three-dimensional point cloud. From the experiment results, we can observe that this method is simple, time-saving and easy to realize.
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