The Fundamentals of Radar with Applications to Autonomous Vehicles

Radar systems can be extremely useful for applications in autonomous vehicles. This paper seeks to show how radar systems function and how they can apply to improve autonomous vehicles. First, the basics of radar systems are presented to introduce the basic terminology involved with radar. Then, the topic of phased arrays is presented because of their application to autonomous vehicles. The topic of digital signal processing is also discussed because of its importance for all modern radar systems. Finally, examples of radar systems based on the presented knowledge are discussed to illustrate the effectiveness of radar systems in autonomous vehicles

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Digital signal processing: the impact of convergence on education, society and design flow

Design and development of real-time, memory and processor hungry digital signal processing systems has for decades been accomplished on general-purpose microprocessors. Increasing needs for high-performance DSP systems made these microprocessors unattractive for such implementations. Various attempts to improve the performance of these systems resulted in the use of dedicated digital signal processing devices like DSP processors and the former heavyweight champion of electronics design – Application Specific Integrated Circuits. The advent of RAM-based Field Programmable Gate Arrays has changed the DSP design flow. Software algorithmic designers can now take their DSP algorithms right from inception to hardware implementation, thanks to the increasing availability of software/hardware design flow or hardware/software co-design. This has led to a demand in the industry for graduates with good skills in both Electrical Engineering and Computer Science. This paper evaluates the impact of technology on DSP-based designs, hardware design languages, and how graduate/undergraduate courses have changed to suit this transition

Experimental detection using cyclostationary feature detectors for cognitive radios

© 2014 IEEE. Signal detection is widely used in many applications. Some examples include Cognitive Radio (CR) and military intelligence. Without guaranteed signal detection, a CR cannot reliably perform its role. Spectrum sensing is currently one of the most challenging problems in cognitive radio design because of various factors such as multi-path fading and signal to noise ratio (SNR). In this paper, we particularly focus on the detection method based on cyclostationary feature detectors (CFD) estimation. The advantage of CFD is its relative robustness against noise uncertainty compared with energy detection methods. The experimental result present in this paper show that the cyclostationary feature-based detection can be robust compared to energy-based technique for low SNR levels

Roadmap on optical security

Postprint (author's final draft

The Impact of Interference on GNSS Receiver Observables – A Running Digital Sum Based Simple Jammer Detector

A GNSS-based navigation system relies on externally received information via a space-based Radio Frequency (RF) link. This poses susceptibility to RF Interference (RFI) and may initiate failure states ranging from degraded navigation accuracy to a complete signal loss condition. To guarantee the integrity of the received GNSS signal, the receiver should either be able to function in the presence of RFI without generating misleading information (i.e., offering a navigation solution within an accuracy limit), or the receiver must detect RFI so that some other means could be used as a countermeasure in order to ensure robust and accurate navigation. Therefore, it is of utmost importance to identify an interference occurrence and not to confuse it with other signal conditions, for example, indoor or deep urban canyon, both of which have somewhat similar impact on the navigation performance. Hence, in this paper, the objective is to investigate the effect of interference on different GNSS receiver observables in two different environments: i. an interference scenario with an inexpensive car jammer, and ii. an outdoor-indoor scenario without any intentional interference. The investigated observables include the Automatic Gain Control (AGC) measurements, the digitized IF (Intermediate Frequency) signal levels, the Delay Locked Loop and the Phase Locked Loop discriminator variances, and the Carrier-to-noise density ratio (C/N0) measurements. The behavioral pattern of these receiver observables is perceived in these two different scenarios in order to comprehend which of those observables would be able to separate an interference situation from an indoor scenario, since in both the cases, the resulting positioning accuracy and/or availability are affected somewhat similarly. A new Running Digital Sum (RDS) -based interference detection method is also proposed herein that can be used as an alternate to AGC-based interference detection. It is shown in this paper that it is not at all wise to consider certain receiver observables for interference detection (i.e., C/N0); rather it is beneficial to utilize certain specific observables, such as the RDS of raw digitized signal levels or the AGC-based observables that can uniquely identify a critical malicious interference occurrence