Due to the frequency constraints imposed by the necessary coexistence of radar and communications, the increasing range resolution requirements of modern radar systems can only be achieved by fusing multiple frequency bands. There are a variety of published approaches to solve this task. In this paper we will present two algorithms, the first one based on a high resolution spectral estimation method and the second one based on a compressive sensing algorithm
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
This thesis develops algorithms and applications for compressive sensing, a topic in signal processi...
Accurate measurement of a multisine waveform is a classic spectral analysis problem. Algorithms base...
A system of co-located narrow-band radars operating in disjoint frequency bands may be viewed as a g...
Existing compressed sensing algorithms fail when applied to radar target detection in the presence o...
To accurately estimate locations and velocities of surrounding targets (cars) is crucial for advance...
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar,...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse sig...
Sensor data fusion techniques have been applied in the recent years to the combination of the inform...
Radar receivers typically employ matched filters designed to maximize signal to noise ratio (SNR) in...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
This book details some of the major developments in the implementation of compressive sensing in rad...
In today's automotive applications, radar is widely used to estimate the target position and velocit...
Increasing resolution is an attractive goal for all types of radar sensor applications. Obtaining h...
In this paper we present some preliminary results on the application of Compressive Sensing (CS) to ...
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
This thesis develops algorithms and applications for compressive sensing, a topic in signal processi...
Accurate measurement of a multisine waveform is a classic spectral analysis problem. Algorithms base...
A system of co-located narrow-band radars operating in disjoint frequency bands may be viewed as a g...
Existing compressed sensing algorithms fail when applied to radar target detection in the presence o...
To accurately estimate locations and velocities of surrounding targets (cars) is crucial for advance...
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar,...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse sig...
Sensor data fusion techniques have been applied in the recent years to the combination of the inform...
Radar receivers typically employ matched filters designed to maximize signal to noise ratio (SNR) in...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
This book details some of the major developments in the implementation of compressive sensing in rad...
In today's automotive applications, radar is widely used to estimate the target position and velocit...
Increasing resolution is an attractive goal for all types of radar sensor applications. Obtaining h...
In this paper we present some preliminary results on the application of Compressive Sensing (CS) to ...
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
This thesis develops algorithms and applications for compressive sensing, a topic in signal processi...
Accurate measurement of a multisine waveform is a classic spectral analysis problem. Algorithms base...