False alarm probability

The performances of order statistic (OS) constant false alarm rate (CFAR) detectors are analyzed for non-Gaussian clutters modeled by heavy-tailed complex isotropic symmetric alpha-stable random processes whose amplitude is the generalized Rayleigh distribution. The detection and false alarm probabilities of the amplitude OS-CFAR detectors are presented assuming that the target signal is Rayleigh distributed. Exact closed-form solutions are derived for

The Bureau of Customs and Border Protection has the task of interdicting illicit radioactive material at ports of entry. Items of concern include radiation dispersal devices (RDD), nuclear warheads, and special nuclear material (SNM). The preferred survey method screens all vehicles in primary and diverts questionable vehicles to secondary. This requires high detection probability in primary while not overwhelming secondary with alarms, which could include naturally occurring radioactive material (NORM) found in acceptable cargo and radionuclides used in medical procedures. Sensitive alarm algorithms must accommodate the baseline depression observed whenever a vehicle enters the portal. Energy-based algorithms can effectively use the crude energy information available from a plastic scintillator to distinguish NORM from SNM. Whenever NORM cargo limits the alarm threshold, energy-based algorithms produce significantly better detection probabilities for small SNM sources than gross-count algorithms. Algorithms can be best evaluated using a large empirical data set to 1) calculate false alarm probabilities, 2) select sigma-level thresholds for operationally acceptable false alarm rates, and 3) determine detection probabilities for marginally detectable pseudo sources of SNM.

This paper investigates the application of the Generalized Likelihood Ratio Test detector to the Global Navigation Satellite System array-based acquisition problem. We consider an unstructured channel model which includes colored noise with an arbitrary covariance matrix. We show that the proposed test function is a Constant False Alarm Rate detector and we provide closed form expressions for false alarm, detection probabilities, and the Receiver Operating Characteristic. Furthermore, this work analyzes the Sample Covariance Matrix structure and the capability of the detector to reject uncorrelated interferences. Simulation results validate the theoretical analysis.

Abstract1-- The Bureau of Customs and Border Pro-tection has the task of interdicting illicit radioactive mate-rial at ports of entry. Items of concern include radiation dispersal devices (RDD), nuclear warheads, and special nuclear material (SNM). The preferred survey method screens all ...

A numerical method for computing the error exponent for Neyman-Pearson detection of two-state Markov chains in noise is presented, for both time-invariant and fading channels. We give numerical studies showing the behaviour of the error exponent as the transition parameters of the Markov chain and the signal-to-noise ratio are varied. Comparisons between the high SNR asymptotics for the time-invariant and fading situations will also be made.

We discuss a Bayesian approach to the analysis of radial velocities in planet searches. We use a combination of exact and approximate analytic and numerical techniques to efficiently evaluate chi-squared for multiple values of orbital parameters, and to carry out the marginalization integrals for a single planet including the possibility of a long term trend. The result is a robust algorithm that is rapid enough for use in real time analysis that outputs constraints on orbital parameters and false alarm probabilities for the planet and long term trend. The constraints on parameters and odds ratio that we derive compare well with previous calculations based on Markov Chain Monte Carlo methods, and we compare our results with other techniques for estimating false alarm probabilities and errors in derived orbital parameters. False alarm probabilities from the Bayesian analysis are systematically higher than frequentist false alarm probabilities, due to the different accounting of the number of trials. We show that upper limits on the velocity amplitude derived for circular orbits are a good estimate of the upper limit on the amplitude of eccentric orbits for eccentricities less than about 0.5.

We report the discovery of HAT-P-24b, a transiting extrasolar planet orbiting the moderately bright V=11.818 F8 dwarf star GSC 0774-01441, with a period P = 3.3552464 +/- 0.0000071 d, transit epoch Tc = 2455216.97669 +/- 0.00024 (BJD_UTC), and transit duration 3.653 +/- 0.025 hours. The host star has a mass of 1.191 +/- 0.042 Msun, radius of 1.317 +/- 0.068 Rsun, effective temperature 6373 +/- 80 K, and a low metallicity of [Fe/H] = -0.16 +/- 0.08. The planetary companion has a mass of 0.681 +/- 0.031 MJ, and radius of 1.243 +/- 0.072 RJ yielding a mean density of 0.439 +/- 0.069 g cm-3 . By repeating our global fits with different parameter sets, we have performed a critical investigation of the fitting techniques used for previous HAT planetary discoveries. We find that the system properties are robust against the choice of priors. The effects of fixed versus fitted limb darkening are also examined. HAT-P-24b probably maintains a small eccentricity of e = 0.052 +0.022 -0.017, whic...

The major concentration of this study is to describe the structure of a C++/MEX solution for robust detection and delineation of arterial blood pressure (ABP) signal events. Toward this objective, the original ABP signal was pre-processed by application of à trous discrete wavelet transform (DWT) to extract several dyadic scales. Then, a sliding window with fixed length was moved on the appropriately selected scale. In each slid, mean, variance, Skewness and Kurtosis values of the excerpted segment were superimposed to generate a newly defined multiple higher order moments (MHOM) metric to be used as the detection decision statistic (DS). Then, after application of an adaptive-nonlinear transformation for making the DS baseline static, the histogram parameters of the enhanced DS were used for regulation of the α-level Neyman–Pearson classifier aimed for false alarm probability (FAP)-bounded delineation of the ABP events. The proposed method was applied to all 18 subjects of the MIT-...

In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6 MHz channel, when the frame duration is 100 ms, and the signal-to-noise ratio of primary user at the secondary receiver is -20 dB, the optimal sensing time achieving the highest throughput while maintaining 90% detection probability is 14.2 ms. This optimal sensing time decreases when distributed spectrum sensing is applied.

In cognitive radio networks, the secondary network (users) are allowed to utilize the frequency bands of primary network (users) when they are not currently being used. To support this function, the secondary users are required to sense the radio frequency environment, and once the primary user is found to be active, the secondary users have to vacate the channel within certain amount of time. There are two parameters related to channel sensing: probability of detection and probability of false alarm. The higher the detection probability, the better the primary users can be protected. However, from the secondary users' perspective, the lower the false alarm probability, the more chances the channel can be reused, thus the higher the achievable throughput for the secondary users. In this paper, we study the fundamental tradeoff between sensing capability and achievable throughput of the secondary users. Particularly, we study the design of sensing slot duration to maximize the achievable throughput for the secondary users under the constraint that the primary users are sufficiently protected. Using energy detection scheme, we prove that there indeed exists an optimal sensing time which provides the best tradeoff. Cooperative sensing is also studied based on the methodology of the proposed sensing-throughput tradeoff. Computer simulations are presented to evaluate the proposed tradeoff methodology.

In this paper, cognitive transmission under quality-of-service (QoS) constraints is studied. In the cognitive radio channel model, it is assumed that the secondary transmitter sends the data at two different fixed rates and power levels, depending on the activity of the primary users, which is determined by channel sensing performed by the secondary users. A state transition model with eight states is constructed to model this cognitive transmission channel. Statistical limitations on the buffer lengths are imposed to take into account the QoS constraints. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. The impact upon the effective capacity of several system parameters, including channel sensing duration, detection threshold, detection and false alarm probabilities, QoS parameters, and fixed transmission rates is investigated. It is noted that the optimal transmission rates are independent of the primary users' activity in the case of perfect channel sensing.

The performances of order statistic (OS) constant false alarm rate (CFAR) detectors are analyzed for non-Gaussian clutters modeled by heavy-tailed complex isotropic symmetric alpha-stable random processes whose amplitude is the generalized Rayleigh distribution. The detection and false alarm probabilities of the amplitude OS-CFAR detectors are presented assuming that the target signal is Rayleigh distributed. Exact closed-form solutions are derived for

This paper investigates the application of the Generalized Likelihood Ratio Test detector to the Global Navigation Satellite System array-based acquisition problem. We consider an unstructured channel model which includes colored noise with an arbitrary covariance matrix. We show that the proposed test function is a Constant False Alarm Rate detector and we provide closed form expressions for false alarm, detection probabilities, and the Receiver Operating Characteristic. Furthermore, this work analyzes the Sample Covariance Matrix structure and the capability of the detector to reject uncorrelated interferences. Simulation results validate the theoretical analysis.