http://ieeexplore.ieee.org TOC Alert for Publication# 7 2012 February 10 48 1 c1 c1 161 48 1 c2 c2 265 48 1 1 2 115 48 1 3 15 1511 48 1 16 26 1773 48 1 27 43 5229 48 1 44 63 6139 K-distribution model. Moreover, we show that the generalized likelihood ratio test (GLRT), which is a popular suboptimum detector because of its constant false-alarm rate (CFAR) property, is an optimum detector for our clutter model in the limit as the tails get extremely heavy. The GLRT-LTD is tested against simulated high-resolution sea clutter data to investigate the dependence of its performance on the various clutter parameters.]]> 48 1 64 77 1200 48 1 78 102 7395 48 1 103 115 3834 48 1 116 129 4330 48 1 130 143 1498 48 1 144 158 2999 48 1 159 169 1536 48 1 170 179 1496 48 1 180 196 2554 48 1 197 214 4703 48 1 215 229 2349 48 1 230 242 3881 C/N₀, code tracking (DLL) error and carrier phase tracking (PLL) error for a receiver affected by CW interference signals. The navigation signal model is applied to GNSS power spectral density (PSD) to interpret spectral line effects within receiver tracking low pass filter, limited by navigation data bits. A scaled envelope model is also introduced to estimate average susceptibility of signal against CW interferences. Numerical results show how the spectral lines and correlator model can affect the tracking performances, and the sensitivity of GNSS signals against the CW interferer is investigated by varying data bit duration or integration time.]]> 48 1 243 258 2425 48 1 259 278 3960 48 1 279 289 963 48 1 290 303 2792 2) control mechanism. The system converts a raw dc input voltage in the range of 15 V to 25 V to a stepped-down and filtered output voltage in the range of 1.5 V to 18 V. A custom designed user programmable control circuitry is implemented on the low leakage, radiation tolerant silicon-on-insulator technology. Silicon carbide junction field effect transistors (JFETs) are used as power switches to sustain extreme operating temperature. The system is prototyped on the aluminum nitride substrate to meet packaging requirements. Design considerations for the planar transformer coupled gate drive are specifically addressed. The system performance is studied based on a 20 V to 3.3 V prototype converter. The demonstrated system has potential market in extreme environment applications like deep space explorations, down-hole geothermal and deep gas reservoir management, etc.]]> 48 1 304 312 2122 48 1 313 328 3088 dq modelling approach is applied to derive individual power system component models and to constitute the corresponding generalized power system model as a powerful and flexible stability analysis tool. The element models can be interconnected in an algorithmic way according to a variety of the architecture selected. Intensive time-domain simulation and experimental results are used to verify the theoretical results. It is also shown how the proposed approach can be used to predict instability due to possible variations in operating points and system parameters.]]> 48 1 329 347 4944 48 1 348 359 1906 48 1 360 374 2254 48 1 375 387 1298 48 1 388 404 6594 48 1 405 418 3248 H_∞ guidance law is proposed to intercept an unknown maneuvering target. By using the modified polar coordinate (MPC), nonlinear relative motion equations only contain three state variables. Then we apply the nonlinear H_∞ control theory into system equations to get an analytic H_∞ guidance law, which has the same expression as true proportional navigation (TPN). The proposed H_∞ guidance law can ensure system L₂ gain less than or equal to a positive constant. Some results of performance analysis including capture region, capture region with acceleration constraint, an integral expression of time-to-go, and miss distance are derived analytically. Particularly, the capture region with acceleration constraint is an important improvement upon the capture region of TPN and is significant for applications. Finally, some numerical examples illustrate the theories clearly, and some simulations are conducted to validate the academic results.]]> 48 1 419 429 1241 T(bold x) as constant as possible. Successful normalization makes sonar signal processing much simpler. For example, in automatic tracking, normalizing increases the probability that true tracks get initiated, and decreases the probability that false tracks get initiated. Normalizers work by estimating the background noise power and dividing T(bold x) by that estimate. The split window normalizer (SWN) is a common method of normalization. The SWN is also known as a cell-averaging constant false alarm rate (CA-CFAR) processor. The SWN normalizes each cell of the data by finding a local noise power estimate, and dividing the cell by that local estimate. The SWN finds a local noise power estimate using data in a window around the cell to be normalized. The SWN assumes the noise is stationary in the window. So, the size of the windows must be chosen so the data is approximately stationary over the window. This limits the total amount of data available to estimate any cell. The normalizer developed in this paper is based on the minimum variance spectral estimator (MVSE). The MVSE is a power spectral density (PSD) estimator that easily extends to multiple dimensions. PSD estimators estimate power as it changes over frequency. This is mathematically similar to estimating power as it changes over range or other independent variable. A normalizer based on a PSD estimator does not assume the background power is stationary. Removing the stationary assumption allows the use of larger data windows to estimate the power of each cell. In fact, we can extend the data win- ows over all the ranges, bearings, and pings to perform a three dimensional (3D) estimate of the background power. This 3D estimate uses more data to estimate the background power than the SWN. The SWN can be extended to multiple dimensions but the data windows it uses are limited by assuming the data is stationary in the window. Since the MVSE normalizer uses more data it should produce a better estimate of the background power. The SWN is compared with the new normalizer using a simple track initiation algorithm developed in this paper. Simulation results indicate the MVSE normalizer is 3 dB to 5 dB more effective than the standard SWN for active sonar normalization.]]> 48 1 430 448 8507 48 1 449 467 3025 48 1 468 476 1261 48 1 477 489 4308 48 1 490 501 2382 48 1 502 513 2801 48 1 514 524 1867 48 1 525 541 3529 CB is full (column) rank - an assumption used in direct adaptive control - it is possible to jointly estimate the input signal and the control system's state. It is not necessary to assume that the control signal is constant and therefore large bandwidth input signals are accommodated. A recursive algorithm for the calculation of the minimum variance estimates of the state and control signal is developed. Similar to classical KF, a linear estimation problem is solved; therefore, the minimum variance estimates of the state and input signal are obtained, and thus, the Cramer-Rao lower bound (CRLB) is attained. The filter's gain is constant and whereas in conventional KF the calculation of the covariance of the state estimation error entails the solution of a Riccati equation, the covariances of the state and input estimation errors are determined here by the solution of a Lyapunov equation, and explicit formulae are obtained.]]> 48 1 542 551 388 48 1 552 571 3440 48 1 572 580 1331 48 1 581 603 5207 48 1 604 619 543 48 1 620 636 600 48 1 637 647 3778 48 1 648 657 2246 48 1 658 672 1275 48 1 673 692 4107 C/N₀)) due to interference, residual differential troposphere error, and the error induced by ionosphere gradients. Without restricting ourselves to classical Gaussian overbounding, we combine their probability density functions (pdfs) to a total pseudo-range error distribution. This distribution is propagated through the GBAS Hatch filter and then mapped into the position domain using a worst case (selected by maximum vertical dilution of precision (VDOP)) of a full 31 satellite constellation with the two most critical satellites failed observed at Braunschweig Airport, Germany. Our calculations yield a significant reduction amounting to 46% of the position domain error at the 1.5 × 10^-7 integrity risk level when compared with the classical Gaussian overbounding approach.]]> 48 1 693 706 1488 48 1 707 728 3394 48 1 729 736 692 48 1 737 748 1712 48 1 749 761 2190 48 1 762 779 6180 48 1 780 793 1407 48 1 794 819 4101 48 1 820 831 2019 48 1 832 849 3180 48 1 850 868 2559 48 1 869 890 1336 48 1 891 905 1349 48 1 906 912 326 48 1 913 916 146 48 1 917 923 1131 48 1 923 926 237 48 1 927 928 90 48 1 c3 c3 74 48 1 c4 c4 133