For a typical FMCW automotive radar system, a new design of baseband signal processing architecture and algorithms is proposed to overcome the ghost targets and overlapping problems in the multi-target detection scenario. To satisfy the short measurement time constraint without increasing the RF front-end loading, a three-segment waveform with different slopes is utilized. By introducing a new pairing mechanism and a spatial filter design algorithm, the proposed detection architecture not only provides high accuracy and reliability, but also requires low pairing time and computational loading. This proposed baseband signal processing architecture and algorithms balance the performance and complexity, and are suitable to be implemented in a real automotive radar system. Field measurement results demonstrate that the proposed automotive radar signal processing system can perform well in a realistic application scenario.

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Design of an FMCW radar baseband signal processing system for automotive application

This paper presents a portable radar system for short-range localization, inverse synthetic aperture radar imaging, and vital sign tracking. The proposed sensor incorporates frequency-modulated continuous-wave (FMCW) and interferometry (Doppler) modes, which enable this radar system to obtain both absolute range information and tiny vital signs (i.e., respiration and heartbeat) of human targets. These two different operation modes can be switched through an on-board microcontroller. To simplify the system, the proposed radar utilizes the audio card of a laptop to sample the baseband signal. The FMCW mode of the radar uses operational-amplifier-based circuits to generate an analog sawtooth signal and a reference pulse sequence (RPS). The RPS is locked to the sawtooth signal to obtain coherence for the radar system. For the interferometry mode, a low-intermediate-frequency modulation method is implemented to avoid the slow vital signs from being distorted by the high-pass filter of the audio card. Several experiments were carried out to reveal the capability and distinct operational features of the proposed portable hybrid radar. The experiments also showed that the system can easily detect glass, which is usually difficult to identify for optical-based sensors. In addition, 2-D scanning in a complex environment revealed that the proposed radar was able to differentiate human targets from other objects. Moreover, ISAR images were used to isolate moving human targets from surrounding clutter. Finally, the proposed radar also demonstrated its ability to accurately measure vital signs when a human subject sits still.

A Portable FMCW Interferometry Radar With Programmable Low-IF Architecture for Localization, ISAR Imaging, and Vital Sign Tracking

This paper will review the main sensor technologies used to create an autonomous vehicle. Sensors are key components for all types of autonomous vehicles because they can provide the data required to perceive the surrounding environment and therefore aid the decision-making process. This paper explains how each of these sensors work, their advantages and disadvantages and how sensor fusion techniques can be utilised to create a more optimum and efficient system for autonomous vehicles.

Sensor Technology in Autonomous Vehicles : A review

Mapping stationary objects and tracking moving targets are essential for many autonomous functions in vehicles. In order to compute the map and track estimates, sensor measurements from radar, lase ...

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Sensor fusion for automotive applications

Radio frequency (RF) based indoor localisation techniques have gained much attention over the past nearly three decades. Such techniques can be classified as active and passive while passive systems can have either device-assisted or device-free characteristics. Device-free localisation can be a prominent research field as it transcends other device-based approaches in certain application scenarios. Accordingly, we have witnessed an influx of IDFL research focusing on multiple disciplines including occupancy, positioning, activity and identity. However, despite the recent emergence of several exciting technologies and corresponding techniques, IDFL faces some important challenges and because of this, we haven’t come across many mainstream commercial products using RF-based IDFL techniques. In this article, we survey the recent progress of IDFL prioritising on indoor positioning. We decompose the localisation dimensions into occupants, space and time, provide a detailed taxonomy and a comprehensive review of these techniques. We divide the state of the art mainly into Wireless Network-based and Radar-based, evaluate the respective technologies and the techniques qualitatively, discuss trends, limitations and also indicate future research directions relevant to this field.

Recent advances in RF-based passive device-free localisation for indoor applications

This paper describes three different continuous wave (CW) radar waveforms which are applied in automotive radar sensors. The radar sensor should be able to detect all objects inside the observation area and to estimate range, radial velocity and azimuth angle simultaneously even in multi target situations. A classical Linear Frequency Modulation (LFM) waveform provides a very high range and velocity resolution. But in multiple target situations so-called ghost targets will occur. Alternatively, a Frequency Shift Keying (FSK) waveform delivers a very high velocity resolution and avoids any ghost target situation but will not resolve targets in range direction. Finally, a combination between LFM and FSK provides simultaneously a high range and velocity resolution, extremely short measurement time and avoids any ghost target situation. It combines the advantages of both FSK and LFM waveforms. In all three cases the azimuth angle estimation is based on two receive antennas and the monopulse technique.

C. Moller

Papers

Radar waveform for automotive radar systems and applications