Leen Sit

A novel technique for interference mitigation in OFDM radar using compressed sensing

This paper presents an OFDM Radar modulation scheme using non-equidistant subcarriers in combination with an adapted compressed sensing (CS) algorithm for interference mitigation in multi-user scenarios. This scheme is aimed especially at automotive applications to counter mutual interference and avoid a decrease in the detection performance of the radar since it is nearly impossible to perfectly allocate non-overlapping spectra to the non cooperating multiple users as an interference mitigation measure. The signal model and signal processing steps will be described in detail followed by simulation and measurement results to demonstrate the performance of the proposed scheme.

Algorithms for synchronization of coherent UWB receivers and their application

In this paper a detailed analysis of an Ultra-Wideband correlation receiver is presented. The synchronization methods are discussed and analyzed in terms of practical realizability. All algorithms are implemented on FPGA and tested with a real UWB transceiver. The measurement results are then evaluated and compared to the ones found in the literature. Finally an application example for the correlation receiver is demonstrated by means of one-way ranging.

MIMO OFDM radar system for drone detection

This paper presents a system setup based on MIMO OFDM radar that can be used for drone detection and detection of unpiloted aerial vehicles (UAVs) in general. In recent years UAVs have become more and more popular not only for commercial use but also as a private gadget. However, these drones can also be misused as a weapon by criminals, spies and terrorists. Therefore many research is done to be able to detect drones and prevent further harm. One possible approach is radar that has already been used successfully in automotive and military applications and offers many advantages like weather and daylight independent operation. It is also possible to detect drones that are emitting no electrical or optical signals. However, there are still many challenges that have to be solved before the implementation of reliably operating systems. This paper presents a system approach based on MIMO OFDM radar that can be used to survey large areas simultaneously and detect flying drones. Additionally, verification measurements with a drone in a real world scenario are presented demonstrating the successful operation of the system.

Performance analysis of various UWB radar approaches for medical diagnostics

In this paper, the challenge of the UWB radar for medical applications is presented in terms of high signal attenuation and multiple reflections in human tissues. Different UWB radar approaches are reviewed in this research. The IR-UWB approaches, the PN approach and the frequency measurement with the Vector Network Analyzer are introduced and discussed. Furthermore, the demonstrators of all of the three approaches are provided. The system performance of these three approaches are verified by measurements in anechoic chamber. The usage of three radar approaches for medical diagnostics are given. The measurement results show that the frequency measurement with the Vector Network Analyzer performs better than the other two approaches in terms of system dynamic range and stability.

Empirical ANN models for 2D direction of arrival estimation

Empirical Artificial Neural Network (ANN) models are developed for Two-Dimensional Direction of Arrival (2D DOA) estimation of a source signal. For that purpose, experimental data obtained from measurements in an anechoic chamber are utilized. Performance of ANN models are compared to 2D MUSIC algorithm in regard to estimation accuracy and speed of calculations. It is demonstrated that the proposed models outperform MUSIC in cases when small number of snapshots are utilized for DOA estimation and at the same time, are more suitable for real-time implementation.