SPS Chicago Chapter Seminar – Adaptive Waveform Design Framework for MIMO Radar Under Practical Constraints – 04-26-2019

ECE 595 Department Seminar Series
SPS Chicago Chapter Seminar
Department of Electrical and Computer Engineering
Speaker: Dr. Christian Hammes, University of Luxombourg

Date: Friday, April 26, 2019
Time: 11:00 AM – 12:00 PM
Location: 238 SES, 845 West Taylor Street, Chicago, IL 60607

Title: Adaptive Waveform Design Framework for MIMO Radar Under Practical Constraints

Abstract: The recent developments in radar technology – powerful signal processors, increased modulation bandwidth and access to higher carrier frequencies – offers enhanced flexibility in waveform design and receiver processing. This provides additional degrees of freedom in the signal design and processing, thereby offering additional avenues to implement interference mitigation. The radar environment is dynamic in general, with the inhomogeneous interference sources changing rapidly both in space and time.  In this context, an adaptive waveform and adaptive receiver design for Multiple-Input-Multiple-Output (MIMO) radar system is a promising way forward towards dynamic interference mitigation.

Even though the technology offers flexibility, the need to commercialize radar elements imposes certain constraints on the platform to ensure commercial viability. In this context, the transmitted waveform has to satisfy practical design constraints imposed by the hardware including discrete phase modulation and limited number of processing chains. These coupled with the dynamic scenarios warrants a rapid signal adaptation with enhanced performance while satisfying the design constraints.

Motivated by the aforementioned requirements, this talk proposes a general framework for MIMO radar signal adaptation under practical design constraints. The transmit antennas are restricted to operate in a multiplex mode, where a fewer number of processing chains are multiplexed across an arbitrary number of transmit antennas. Each of these chains, also referred to as channels, have the capability to modulate the phase of a traditional radar pulse in discrete steps. Further, the modulation is assumed to be in the slow time domain (inter-pulse); such a phase modulation results in benign requirements on the platform. Furthermore, the antennas are assumed to be mounted uniformly in a way that the virtual MIMO paradigm for maximum angular resolution is satisfied.

The slow time modulation naturally results in an angle-Doppler coupling; this issue is addressed by phase center motion (PCM) techniques, where a random PCM technique for mitigating angle-Doppler coupling is proposed. While the PCM technique provides orthogonal signals, a transmit beamforming approach is also considered to exploit the salient features of MIMO and phased array radars. Towards this, an approach based on block circulant decomposition for the slow-time modulation is proposed to generate a particular beam shape while minimizing the cross-correlation between transmitted signals, such that the virtual MIMO paradigm is satisfied. The radiation pattern design is formulated as a dictionary based convex optimization and proposes closed-form signal design solutions for particular configuration of channels, discrete phase stages and transmit antenna elements. The beam pattern design is then elegantly combined with the PCM approach to reduce Doppler ambiguity while suppressing angle-Doppler coupling. The proposed waveform design methodology is shown to be amenable to fast adaptation.

Bio: Christian Hammes is from Trier, Germany and working as a Research Associate in the Signal Processing and Satellite Communication department at the Interdisciplinary Centre for Security, Reliability and Trust (SnT). He obtained his Ph.D. degree in Computer Science from the University of Luxembourg (SnT) in 2019. His research interests include radar and signal processing under practical constraints.


More info on his work can be found at:
https://wwwen.uni.lu/snt/people/christian_hammes

Host: Dr. Mojtaba Soltanalian, Assistant Professor, msol@uic.edu

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