Doppler Spectrum Parameter Estimation for Weather Radar Echoes Using a Parametric Semianalytical Model

The problem of the limited accuracy of precipitation Doppler spectrum moments estimation measured by fast azimuthally scanning weather radars is addressed. A novel approach for the Doppler moment estimation based on maximum likelihood estimation is proposed. A simplified semianalytical parametric model for the precipitation power spectral...

Precipitation Doppler Spectrum Reconstruction With Gaussian Process Prior

The challenge of reconstructing the Doppler spectrum of a precipitation-like event observed by a fast-scanning weather radar is addressed. A novel method is proposed where the echo sequence in time is assumed to be a complex Gaussian process with a known covariance structure. It is a two-step approach where the first step is the estimation of...

Data-association-free Characterization of Labeling Uncertainty: The Cross Modeling Tracker

The Multiple Object Tracking problem for a known and constant number of closely-spaced objects in a track-before-detect context is considered. The underlying problem of decomposing a dataassociation- free Bayes posterior density is analyzed. A previously proposed solution for two objects moving in one-dimensional space is generalized for...

A Constrained POMDP Formulation and Algorithmic Solution for Radar Resource Management in Multi-Target Tracking

The radar resource management problem in a multitarget tracking scenario is considered. The problem is solved using a dynamic budget balancing algorithm. It models the different sensor tasks as partially observable Markov decision processes and solves them by applying a combination of Lagrangian relaxation and policy rollout. The algorithm has a...

Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation

The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on...

Multi-Task Sensor Resource Balancing Using Lagrangian Relaxation and Policy Rollout

The sensor resource management problem in a multi-object tracking scenario is considered. In order to solve it, a dynamic budget balancing algorithm is proposed which models the different sensor tasks as partially observable Markov decision processes. Those are being solved by applying a combination of Lagrangian relaxation and policy rollout....

Wind turbine angular velocity estimation using polarimetry

Wind turbines usually cause significant interference in the conventional radar operations which might degrade the detection capabilities. Wind turbines do not only block the radar beam focusing on a specific target, thus creating shadowing effects, but also impose Doppler spectra contamination due to the continuous blade rotation. Therefore...

Target Selection for Tracking in Multifunction Radar Networks: Nash and Correlated Equilibria

We consider a target selection problem for multitarget tracking in a multifunction radar network from a gametheoretic perspective. The problem is formulated as a noncooperative game. The radars are considered to be players in this game with utilities modeled using a proper tracking accuracy criterion and their strategies are the observed...

Using Golay Sequences to Improve the Range Performance of Hybrid Codes for MIMO Radar

In this paper, waveforms for MIMO phased array radar to enhance cross-range resolution are investigated. The problem of high sidelobes in range created by the use of Hybrid Codes with a single waveform and spatial coding is considered and a method to reduce these sidelobes by the use of Golay sequences as spatial codes is proposed. It is shown...

Human motion classification using a particle filter approach: Multiple model particle filtering applied to the micro-Doppler spectrum

In this article, a novel motion model-based particle filter implementation is proposed to classify human motion and to estimate key state variables, such as motion type, i.e. running or walking, and the subject’s height. Micro-Doppler spectrum is used as the observable information. The system and measurement models of human movements are built...