Special Issue "Radar and Information Theory"
Deadline for manuscript submissions: closed (20 December 2017).
Interests: modeling; statistical signal processing; information theory; machine learning; sensor networks and fusion; sparse recovery; compressive sensing; optimal design; applications to radar, sonar and biomedicine
Interests: statistical signal processing, information theory, network fusion, compressive sensing, optimal design, machine learning, and their applications to radar, communication, and sensor arrays
Interests: statistical signal processing, machine learning, information theory, and their applications in radar, brain computer interfaces, and health informatics
Information theory has been applied in radar signal processing for over a half a century now, starting from the pioneering work of Woodward and Davies. However, the research on information theory for radar applications, initially, was not as effective as it had been in communication areas, due to the inherent differences in the concept of “information” in these two fields. The sole purpose of the radar systems is to seek information about a target, which is, in general, non-cooperative, whereas communication systems aim to extract information regarding a transmitting signal/message. Then, with the seminal dissertation work by Bell, information theory regained its footing in radar signal processing to adaptively design the transmitting waveform, which can extract more target-information from the received measurements. Henceforth, information theoretic criteria, especially mutual information and relative entropy (also known as Kullback-Leibler divergence), have been at the core of adaptive radar waveform design algorithms. Additionally, with the recent emergence of cognitive radar, which learns from its experience in addition to sensing and adapting, the concept of information preservation has become even more relevant in the radar receiver processing chain.
Therefore, the aim of this Special Issue is to encourage researchers to present original and recent developments on information theory for the advanced radar systems and algorithms. Applications can include (but are not limited to) target detection, tracking, parameter estimation, target recognition and classification, synthetic/inverse-synthetic radar imaging, electronic counter/counter-counter measures, and adaptive/cognitive waveform design. Analytical development of radar performance bounds/limits, analogous to those in communication, such as Shannon’s theorem, Slepian-Wolf theorem, rate-distortion theory, etc., is also encouraged.
Prof. Dr. Arye Nehorai
Prof. Dr. Murat Akcakaya
Dr. Satyabrata Sen
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- radar signal processing
- information theoretic measures and criteria
- information preservation
- entropy, relative entropy, mutual information
- Shannon’s theorem, Slepian-Wolf theorem, rate-distortion theory
- target detection and tracking
- target recognition and classification
- parameter estimation and feature extraction
- adaptive and cognitive radar waveform design
- synthetic/inverse-synthetic radar imaging
- information theoretic radar performance bounds