Estimation of Moving Target Parameters using Compressive Sensing Methods

Abstract—The parameter estimation of a distributed target with several moving elements is an important question in radar based security applications. In this paper, a solution of this problem is proposed by using an incoherent radar sensor network as well as signal processing methods known from the area of Compressive Sensing. Thereby, three different algorithms are evaluated: Orthogonal Matching Pursuit (OMP), SIMPLEX and nonlinear Convex Optimization. It can be shown that a relative small number of radar channels is sufficient to determine positions and velocity vectors of many point scatterers included in the analyzed scene

Increased traffic safety by means of intelligent detection and localization technologies

The two technologies presented in this paper, "Communication Location Surveillance" (CLS) and radar classification by means of evaluation of micro-Doppler spectra, have been adapted and further developed for use in critical and complex traffic situations. The aim of the joint research activity of DLR and IMST is to detect potentially dangerous traffic situations at an early stage and, in particular, to protect vulnerable road users who do not usually communicate digitally with other road users. This is done by precisely locating road users and recording their direction of movement and speed. On the other hand, it must be possible to classify the participants in order to be able to assess their particular potential danger. Only with an exact situation overview of a traffic situation can predictions be made to assess the danger and possible countermeasures be initiated. This includes, for example, warnings to the participants via acoustic or optical signals, via digital vehicle communication or active intervention in a traffic light control system