In this paper, radar detection based on Monte Carlo sampling is studied. Two detectors based on Importance Sampling are presented. In these detectors, called Particle Detector, the approximated likelihood ratio is calculated by Monte Carlo sampling. In the first detector, the unknown parameters are first estimated and are substituted in the likelihood ratio (like &#10the GLRT method). In the s...

In this paper, radar detection based on Monte Carlo sampling is studied. Two detectors based on Importance Sampling are presented. In these detectors, called Particle Detector, the approximated likelihood ratio is calculated by Monte Carlo sampling. In the first detector, the unknown parameters are first estimated and are substituted in the likelihood ratio (like the GLRT method). In the sec...

in this paper, an interference management for multi-beam satellite network to enhance spectral efficiency is studied. first, a two-satellite for future generation satellite network using cognitive radio technology is provided.this network is composed of a secondary satellite and aprimary satellite where the primary satellite system does not suffer from severe destructive interferences coming fr...

A detector for the case of a radar target with known Doppler and unknown complex amplitude in complex Gaussian noise with unknown parameters has been derived. The detector assumes that the noise is an Auto-Regressive (AR) process with Gaussian autocorrelation function which is a suitable model for ground clutter in most scenarios involving airborne radars. The detector estimates the unknown...

in this paper, the detection of moving targets in airborne widely separated phased multiple input multiple output (mimo) radars which are located on moving platform is investigated. in order to derive the detector, the generalized likelihood ratio test is applied. the proposed detection rule, exploits the clutter subspace information and its maximum likelihood estimation, to improve the detecti...

We consider discrete-time detection with dynamical modeling, where the data generating processes are represented through state-variable techniques. Given the modeling above, one computationally effective method of calculating the likelihood ratio functions is due to Schweppe. In this paper, we study the asymptotic properties of Schweppe’s likelihood ratio detector, and evaluate the power probab...

We derive a detector function for quantum two-mode squeezing (QTMS) radars and noise that is based on the use of likelihood ratio (LR) test distinguishing between presence absence target. In addition to an explicit expression LR detector, we which approximates in limit where target small, far away, or otherwise difficult detect. When number integrated samples large, theoretical receiver operati...

The problem of detecting a signal known except for amplitude in incompletely characterized colored non-Gaussian noise is addressed. The problem is formulated as a testing of composite hypotheses using parametric models for the statistical behavior of the noise. A generalized likelihood ratio test is employed. It is shown that for a symmetric noise probability density function the detection perf...