A novel Nyquist Folding Receiver (NYFR) based passive localization algorithm with Sparse Bayesian Learning (SBL) is proposed to estimate the position of a spaceborne Synthetic Aperture Radar (SAR).Taking the geometry and kinematics of a satellite into consideration, this paper presents a surveillance geometry model, which formulates the localization problem into a sparse vector recovery problem. A NYFR technology is utilized to intercept the SAR signal. Then, a convergence algorithm with SBL is introduced to recover the sparse vector. Furthermore, simulation results demonstrate the availability and performance of our algorithm.

This paper proposes a novel RBF training algorithm based on immune operations for dynamic problem solving. The algorithm takes inspiration from the dynamic nature of natural immune system and locally-tuned structure of RBF neural network. Through immune operations of vaccination and immune response, the RBF network can dynamically adapt to environments according to changes in the training set. Simulation results demonstrate that RBF equalizer based on the proposed algorithm obtains good performance in nonlinear time-varying channels.

Nyquist folding receiver (NYFR) is a novel reconnaissance receiving architecture and it can realize wideband receiving with small amount of equipment. As a tradeoff of non-cooperative wideband receiving, the NYFR output will add an unknown key parameter that is called Nyquist zone (NZ) index. In this letter, we concentrate on the NZ index estimation of the NYFR output. Focusing on the basic pulse radar signals, the constant frequency signal, the binary phase coded signal and the linear frequency modulation signal are considered. The matching component function is proposed to estimate the NZ indexes of the NYFR outputs without the prior information of the signal modulation type. In addition, the relations between the matching component function and the parameters of the NYFR are discussed. Simulation results demonstrate the efficacy of the proposed method.

This paper presents a new GPU-based rasterization algorithm for Boolean operations that handles arbitary closed polygons. We construct an efficient data structure for interoperation of CPU and GPU and propose a fast GPU-based contour extraction method to ensure the performance of our algorithm. We then design a novel traversing strategy to achieve an error-free calculation of intersection point for correct Boolean operations. We finally give a detail evaluation and the results show that our algorithm has a higher performance than exsiting algorithms on processing polygons with large amount of vertices.

This letter considers a multiple-channel cognitive radio network (CRN) which can simultaneously sense multiple narrowband channels at a time. Taking the maximization of the CRN's overall throughput as the design objective, the optimization problem of jointly designing sensing time, sensing thresholds and transmission power allocation is formulated under the total power constraint of the CRN and the average interference constraint of the primary network. An iterative algorithm is proposed to obtain the locally optimal values for these parameters. Finally, numerical results show that significant overall throughput gain is achieved through the joint design.

This letter proposes a Light Space Partitioned Shadow Maps (LSPSMs) algorithm which implements shadow rendering based on a novel partitioning scheme in light space. In stead of splitting the view frustum like traditional Z-partitioning methods, we split partitions from the projection of refined view frustum in light space. The partitioning scheme is performed dual-directionally while limiting the wasted space. Partitions are created in dynamic number corresponding to the light and view directions. Experiments demonstrate that high quality shadows can be rendered in high efficiency with our algorithm.

A fast parameter estimation method with a coarse estimation and a fine estimation for polyphase P coded signals is proposed. For a received signal with N sampling points, the proposed method has an improved performance when the signal-to-noise ratio (SNR) is larger than 2dB and a lower computational complexity O(N logs N) compared with the latest time-frequency rate estimation method whose computational complexity is O(N2).

This letter proposes a track before detect scheme embedded in coherent repeated interference with the aid of frequency diversity array. The unmatched properties between echo and interferences are firstly discussed from both signal processing and data processing standpoints. Afterward, the interference suppression algorithm with virtual channel weighting at continue sampling stage is proposed, followed with kinematics constraint correspondingly. Further, the evaluations of the interference suppression performance are carried out through simulations which illustrate the feasibility and validity of the proposed algorithm.

To improve detection performance for a reconnaissance receiver, which is designed to detect the non-cooperative MIMO-LFM radar signal under low SNR condition, this letter proposed a novel signal detection method. This method is based on Fractional Fourier Transform with entropy weight (FRFTE) and autocorrelation algorithm. In addition, the flow chart and feasibility of the proposed algorithm are analyzed. Finally, applying our method to Wigner Hough Transform (WHT), we demonstrate the superiority of this method by simulation results.

Vector data differs in the rasterized height field by data type. It is difficult to render dynamic vectors on height field because their shapes and locations may change at any time. This letter proposes a novel method: View-dependent Projective Atlases (VdPAs). As an intermediate data source, VdPAs act as rendering targets which enable height field and vectors to be rasterized at the same resolution. Then, VdPAs can be viewed as super-tiles. State of art height field rendering algorithms can be used for scenario rendering. Experimental results demonstrate that atlases are able to make dynamic vectors to be rendered on height field with real-time performance and high quality.