With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection met...

Sequential Bayesian estimation for nonlinear dynamic state-space models involves recursive estimation of filtering and predictive distributions of unobserved time varying signals based on noisy observations. This paper introduces a new filter called the Gaussian particle filter1. It is based on the particle filtering concept, and it approximates the posterior distributions by single Gaussians, ...

Particle filter and Gaussian mixture implementations of random finite set filters have been proposed to tackle the issue of jointly estimating the number of targets and their states. The Gaussian mixture PHD (GM-PHD) filter has a closed-form expression for the PHD for linear and Gaussian target models, and extensions using the extended Kalman filter or unscented Kalman Filter have been develope...

By using a pulse amplitude modulation representation of the binary continuous phase modulation signals, we develop a new optimum Viterbi sequence detector and a near optimum Viterbi receiver with low complexity. Also, for the modulation index 0.5 where a linear receiver can be used, a minimum mean-squared error linear receiver filter is derived. Their performance is analyzed. The Gaussian minim...

A new Gaussian mixture filter has been developed, one that uses a re-sampling step in order to limit the covariances of its individual Gaussian components. The new filter has been designed to produce accurate solutions of difficult nonlinear/nonBayesian estimation problems. It uses static multiple-model filter calculations and Extended Kalman Filter (EKF) approximations for each Gaussian mixand...

Modern databases tailored to highly distributed, fault tolerant management of information for big data applications exploit a classical data structure for reducing disk and network I/O as well as for managing data distribution: The Bloom filter. This data structure allows to encode small sets of elements, typically the keys in a key-value store, into a small, constant-size data structure. In or...

In INS (Inertial Navigation System) /GPS (Global Positioning System) integration, nonlinear models should be properly handled. The most popular and commonly used method is the Extended Kalman Filter (EKF) which approximates the nonlinear state and measurement equations using the first order Taylor series expansion. On the other hand, recently, some nonlinear filtering methods such as Gaussian S...

As the distribution of the multiuser interference plus noise in time-hopping ultrawide bandwidth (TH-UWB) systems can not be reliably approximated by Gaussian probability density function (PDF), the bit error rate (BER) performance of the conventional matched filter receiver in TH-UWB multiuser systems degrades. In this paper we study a novel TH-UWB receiver based on two PDFs approximating the ...

With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection met...

Image is a multimedia component rich in information and has an essential role as provider. However, the images encountered often experience decrease quality, such defects or noise, causing conveyed from these less clear. Noise causes image to be too contrasted, blurry, not sharp enough. One type of noise contrast noise. Smoothing here one operations improve quality which aims smooth out with un...