Radar Signal Processing for Interference Mitigation

Authors

Zhe Geng, Florida International UniversityFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Electrical Engineering

First Advisor's Name

Hai Deng

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Malek Adjouadi

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Jean Andrian

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Ismail Guvenc

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Deng Pan

Fifth Advisor's Committee Title

Committee Member

Keywords

Radar, signal processing, interference mitigation

Date of Defense

3-23-2018

Abstract

It is necessary for radars to suppress interferences to near the noise level to achieve the best performance in target detection and measurements. In this dissertation work, innovative signal processing approaches are proposed to effectively mitigate two of the most common types of interferences: jammers and clutter. Two types of radar systems are considered for developing new signal processing algorithms: phased-array radar and multiple-input multiple-output (MIMO) radar. For phased-array radar, an innovative target-clutter feature-based recognition approach termed as Beam-Doppler Image Feature Recognition (BDIFR) is proposed to detect moving targets in inhomogeneous clutter. Moreover, a new ground moving target detection algorithm is proposed for airborne radar. The essence of this algorithm is to compensate for the ground clutter Doppler shift caused by the moving platform and then to cancel the Doppler-compensated clutter using MTI filters that are commonly used in ground-based radar systems. Without the need of clutter estimation, the new algorithms outperform the conventional Space-Time Adaptive Processing (STAP) algorithm in ground moving target detection in inhomogeneous clutter.

For MIMO radar, a time-efficient reduced-dimensional clutter suppression algorithm termed as Reduced-dimension Space-time Adaptive Processing (RSTAP) is proposed to minimize the number of the training samples required for clutter estimation. To deal with highly heterogeneous clutter more effectively, we also proposed a robust deterministic STAP algorithm operating on snapshot-to-snapshot basis. For cancelling jammers in the radar mainlobe direction, an innovative jamming elimination approach is proposed based on coherent MIMO radar adaptive beamforming. When combined with mutual information (MI) based cognitive radar transmit waveform design, this new approach can be used to enable spectrum sharing effectively between radar and wireless communication systems.

The proposed interference mitigation approaches are validated by carrying out simulations for typical radar operation scenarios. The advantages of the proposed interference mitigation methods over the existing signal processing techniques are demonstrated both analytically and empirically.

Identifier

FIDC006569

ORCID

0000-0002-5440-3556

Recommended Citation

Geng, Zhe, "Radar Signal Processing for Interference Mitigation" (2018). FIU Electronic Theses and Dissertations. 3571.
https://digitalcommons.fiu.edu/etd/3571