Search

As an important detection means, radar is widely used in target monitoring field. However, due to the small radar cross section (RCS) of stealthy or small target and the complex detection environment, the target echo signal is usually submerged in the environmental clutter. Then the target detection based on Pulse-Doppler radar shows the characteristics of weak signal detection. In this paper, the multi-fold high-order cumulant (HOC) on the radar range-Doppler (R-D) map is proposed to elevate the detection performance of the weak target signal, which can effectively eliminate the noise. Then the processed signal is sent to the CFAR detector to estimate the targets' range and velocity. Although HOC has been used in radar signal detection, the detection algorithm was mainly done on the processed signal after one-fold HOC. We propose a construction method of multi-fold HOC using a set of delay vectors to further eliminate residual noise after one-fold HOC processing. Our proposed multi-fold HOC can be seen as a data preprocessing method, which can also be applied to other detection algorithm to further improve its detection performance. Simulation results show that the proposed multi-fold HOC based CFAR algorithm can greatly reduce SNR required for signal detection, and has an advantage in radar weak signal detection. [ABSTRACT FROM AUTHOR]

A gravitational wave inspirai search with a global network of interferometers when carried in a phase coherent fashion mimics a search with two effective synthetic data streams. The streams are constructed by the linear combination of the overwhitened data from individual detectors. We demonstrate here that the two synthetic data streams pertaining to the two polarizations of the gravitational wave can be derived prior to the maximum-likelihood analysis in a most natural way using the technique of singular-value decomposition applied to the network signal-to-noise ratio vector. The singular-value technique combined with the matched filtering in network plus spectral space enables the construction of the synthetic streams. We further show that the network log likelihood ratio is then the sum of the log-likelihood ratios of these synthetic streams. In this formalism, the four extrinsic parameters of the nonspinning inspirai signal, namely, amplitude, initial phase, binary inclination, and the polarization {A0,Փa, ∊,Ψ} are mapped to the two amplitudes and two phases, namely, {pL,pRՓL,ՓR}, We show that the maximization over the new extrinsic parameters is a straightforward exercise closely linked to the single detector approach in the literature. Toward the end, we connect all the previous works related to the multidetector gravitational wave inspirai search and present in the same notation. [ABSTRACT FROM AUTHOR]

We describe the implementation of a search for gravitational waves from compact binary coalescences in LIGO and Virgo data. This all-sky, all-time, multidetector search for binary coalescence has been used to search data taken in recent LIGO and Virgo runs. The search is built around a matched filter analysis of the data, augmented by numerous signal consistency tests designed to distinguish artifacts of non- Gaussian detector noise from potential detections. We demonstrate the search performance using Gaussian noise and data from the fifth LIGO science run and demonstrate that the signal consistency tests are capable of mitigating the effect of non-Gaussian noise and providing a sensitivity comparable to that achieved in Gaussian noise. [ABSTRACT FROM AUTHOR]

We derive explicit expressions for the multidetector F-statistic metric applied to short-duration nonprecessing inspirai signals. This is required for template bank production associated with coherent searches for short-duration nonprecessing inspirai signals in gravitational-wave data from a network of detectors. We compare the metric's performance with explicit overlap calculations for all relevant dimensions of parameter space and find the metric accurately predicts the loss of detection statistic above overlaps of 95%. We also show the effect that neglecting the variations of the detector response functions has on the metric. [ABSTRACT FROM AUTHOR]