Applied Signal Technology is a provider of advanced intelligence, surveillance and reconnaissance products, systems, and services, established in 1984 in Sunnyvale, California. Its 2009 revenue was $202.6 million with a profit of $22.9 million. Its current President and CEO is William B. Van Vleet III. AST serves the defense, intelligence, homeland security, and select commercial markets.Its products are used to scan and filter cell phone, ship-to-shore, microwave, and military transmissions and evaluate them for relevant information.In December 2010, AST agreed to be acquired by military contractor Raytheon for $490 million. Wikipedia.
Davenport M.A.,Georgia Institute of Technology |
Laska J.N.,Dropcam Inc. |
Treichler J.R.,Applied Signal Technology |
Baraniuk R.G.,Rice University
IEEE Transactions on Signal Processing | Year: 2012
Compressive sensing (CS) exploits the sparsity present in many signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, in theory, commensurate reductions in the size, weight, power consumption, and/or monetary cost of both signal sensors and any associated communication links. This paper examines the use of CS in the design of a wideband radio receiver in a noisy environment. We formulate the problem statement for such a receiver and establish a reasonable set of requirements that a receiver should meet to be practically useful. We then evaluate the performance of a CS-based receiver in two ways: via a theoretical analysis of its expected performance, with a particular emphasis on noise and dynamic range, and via simulations that compare the CS receiver against the performance expected from a conventional implementation. On the one hand, we show that CS-based systems that aim to reduce the number of acquired measurements are somewhat sensitive to signal noise, exhibiting a 3 dB SNR loss per octave of subsampling, which parallels the classic noise-folding phenomenon. On the other hand, we demonstrate that since they sample at a lower rate, CS-based systems can potentially attain a significantly larger dynamic range. Hence, we conclude that while a CS-based system has inherent limitations that do impose some restrictions on its potential applications, it also has attributes that make it highly desirable in a number of important practical settings. © 1991-2012 IEEE. Source
Applied Signal Technology | Date: 2013-06-07
A method for target detection includes: receiving input data via an input signal; generating a histogram from the received data by a processor; rank-ordering the received data based on power or amplitude of the received input signal; comparing the ranked data received in a current time period to the ranked data received in a previous time period to calculate a Bivariate Conditional Exceedance function (BCEF); utilizing the calculated BCEF to estimate a Gumbel Copula parameter; accumulating a log-likelihood statistic from the estimated Gumbel Copula parameter and the generated histogram; comparing the log-likelihood statistic with a threshold value; and determining a detection of the target, when the log-likelihood statistic is below the threshold value.
Applied Signal Technology | Date: 2010-04-30
A method and apparatus for fractional digital integration of an input signal is provided, the input signal including a time series of numerical values and the method or apparatus including applying the input signal time series to one input of a two-input summer at a time I, providing an output of the summer to a delay register at time I, providing an output of the delay register from time i1 to a two-input multiplier, providing an output of the multiplier to the summer at time I, using a resettable counter to determine a value i and index a lookup table with i to provide the indexed value of the lookup table as an input to the multiplier, and obtaining an output signal time series from the output of the summer.
Applied Signal Technology | Date: 2010-04-30
Applied Signal Technology | Date: 2011-10-31
A system for correcting for an angle of rotation between a linearly polarized target signal and a dual-polarized antenna having vertical and horizontal outputs includes receiving a time series of signals from the vertical and horizontal outputs of the receive antenna, applying the vertical signals simultaneously to a data buffer and to a spectrum domain converter block to yield, respectively, spectral Xv(n) and Xv(k) signals, applying the horizontal signals simultaneously to a data buffer and to a spectrum domain converter block to yield, respectively, spectral Xh(n) and Xh(k) signals, detecting the angle of rotation, applying the angle of rotation and the Xv(k) and Xh(k) signals to a polarization rotation correction block to obtain polarization corrected frequency data, and applying the detected angle of rotation and the Xv(n) and Xh(n) signals to a polarization rotation correction block to obtain polarization corrected time data.