Christopher J. Baker

Radar Spectrum Engineering and Management: Technical and Regulatory Issues

The radio-frequency (RF) electromagnetic spectrum, extending from below 1 MHz to above 100 GHz, represents a precious resource. It is used for a wide range of purposes, including communications, radio and television broadcasting, radionavigation, and sensing. Radar represents a fundamentally important use of the electromagnetic (EM) spectrum, in applications which include air traffic control, geophysical monitoring of Earth resources from space, automotive safety, severe weather tracking, and surveillance for defense and security. Nearly all services have a need for greater bandwidth, which means that there will be ever-greater competition for this finite resource. The paper explains the nature of the spectrum congestion problem from a radar perspective, and describes a number of possible approaches to its solution both from technical and regulatory points of view. These include improved transmitter spectral purity, passive radar, and intelligent, cognitive approaches that dynamically optimize spectrum use.

Cognitive Radar Framework for Target Detection and Tracking

Most radar systems employ a feed-forward processing chain in which they first perform some low-level processing of received sensor data to obtain target detections and then pass the processed data on to some higher-level processor such as a tracker, which extracts information to achieve a system objective. System performance can be improved using adaptation between the information extracted from the sensor/processor and the design and transmission of subsequent illuminating waveforms. As such, cognitive radar systems offer much promise. In this paper, we develop a general cognitive radar framework for a radar system engaged in target tracking. The model includes the higher-level tracking processor and specifies the feedback mechanism and optimization criterion used to obtain the next set of sensor data. Both target detection (track initiation/termination) and tracking (state estimation) are addressed. By separating the general principles from the specific application and implementation details, our formulation provides a flexible framework applicable to the general tracking problem. We demonstrate how the general framework may be specialized for a particular problem using a distributed sensor model in which system resources (observation time on each sensor) are allocated to optimize tracking performance. The cognitive radar system is shown to offer significant performance gains over a standard feed-forward system.

Fully Adaptive Radar for Target Tracking Part I: Single Target Tracking

Most radar systems employ a feed-forward processing chain in which they first perform some low-level processing of received sensor data to obtain target detections and then pass the processed data on to some higher-level processor such as a tracker, which extracts information to achieve a system objective. System performance can be improved using adaptation between the information extracted from the sensor/processor and the design and transmission of subsequent illuminating waveforms. As such, cognitive or fully adaptive radar systems offer much promise. In this paper, we develop a general fully adaptive radar framework for a radar system engaged in target tracking. The model includes the higher-level tracking processor and specifies the feedback mechanism and optimization criterion used to obtain the next set of sensor data. Performance is demonstrated on a distributed sensor system in which system resources (observation time on each sensor) are allocated to optimize single target tracking performance.

Fully adaptive radar for target tracking part II: Target detection and track initiation

Most radar systems employ a feed-forward processing chain in which they first perform some low-level processing of received sensor data to obtain target detections and then pass the processed data on to some higher-level processor such as a tracker, which extracts information to achieve a system objective. System performance can be improved using adaptation between the information extracted from the sensor/processor and the design and transmission of subsequent illuminating waveforms. As such, cognitive or fully adaptive radar systems offer much promise. In Part I of this work, we developed a general fully adaptive radar framework and specialized the model for single target tracking. In this paper (Part II), the general framework is specialized for target detection and track initiation. Performance is demonstrated on a distributed sensor system in which system resources (observation time on each sensor) are allocated to optimize new target detection performance.

Cognitive radar for target tracking using a software defined radar system

Most radar systems employ a feed-forward processing chain in which they first perform some low-level processing of received sensor data to obtain target detections and then pass the processed data on to some higher-level processor such as a tracker. Cognitive radar systems use adaptation between the information extracted from the sensor/processor and the design and transmission of subsequent illuminating waveforms. In this paper, we develop a cognitive radar tracking system based on the Maximum a Posteriori Penalty Function (MAP-PF) tracking methodology, which allows us to cognitively control both the radar sensor and the processor. We demonstrate performance for a pulse-Doppler radar system in which the pulse repetition frequency is adjusted to optimize tracking performance, while keeping the target from being Doppler-aliased and away from the zero-Doppler clutter. Results are shown on experimentally collected data using a software defined radar system.

Investigations toward multistatic passive radar imaging

Potential for imaging in passive multistatic radar systems is investigated primarily in terms of illuminator type and coherency. A typical set of transmitters in the UHF and VHF bands based upon the local illuminators in the Columbus, Ohio region is presented to constitute a realistic passive imaging environment. A passive radar signal model is then developed and demonstrates one possible processing implementation for imaging across multiple distributed illuminators. From this, the spatial frequency representation of an airborne target traversing a common flight path is presented. This k-space formulation is assessed as a tool for predicting imaging performance, along with potential limitations of the approach for accurately modeling realistic imaging scenarios of multistatic passive radar systems. Finally, simulation results show the -3 dB point target response to be <;1 m for FM transmitters and <;0.2 m for DTV, for the realistic Columbus-based imaging environment.

Performance analysis of time division and code division waveforms in co-located MIMO

Multiple Input Multiple Output (MIMO) beamforming holds much promise as a concept appropriate for a variety of radar applications. In this paper, MIMO beamforming is examined both theoretically and experimentally in order to highlight fundamental differences in performance between the time division and the code division forms of multiplexing (TDM and CDM). There are significant differences in system performance due to limits on the orthogonality of waveforms that occur when using CDM. These limits are manifested in the peak-to-mean sidelobe correlation ratio, resulting in extended range sidelobes.

Reliable target feature extraction and classification using potential target information

A reliable target feature extraction process is proposed in this paper. The locations of dominant scatterers have been widely adopted as target features in automatic target recognition (ATR) systems. However, the direct use of the locations shows high variability and results in a negative effect on target classification performance. Here, we propose a novel grid cell structure that uses information regarding potential targets to be classified. The grid cell structure extracts stable features from SAR images with a relatively lower computational complexity. A novel target feature that uses information about the variability of scatterers is also proposed. Simulation results, using real target measurements taken from the MSTAR dataset, demonstrate that the new feature vectors improve classification performance.

Direct signal suppression schemes for passive radar

Passive radar systems must detect the presence of a target response many orders of magnitude weaker than the direct signal interference. Even when digitally modulated waveforms with favorable ambiguity surfaces are employed, the floor of the ambiguity surface sets significant limitations on the minimum detectable signal. Suppression of this direct path and close-in clutter from the surveillance waveform is crucial for maximizing the dynamic range which increases the useful detection range of the system. Presented here is an evaluation of various direct signal suppression schemes - both block and adaptive filtering - tested against various metrics on experimental collected passive radar data using North American digital television (DTV) waveforms. Results show the fast block least-mean squares adaptive filter to be significantly faster than existing algorithms with superior suppression performance. Strategies for selecting filtering schemes depending on the task at hand are also discussed.

Assessing the potential for spectrum sharing between communications and radar systems in the L-band portion of the RF spectrum allocated to radar

The theoretical feasibility of dynamic spectrum sharing between rotating radar and wireless communications systems in L-band is investigated via numerical analyses in this paper. The temporal variations of interference power due to periodic rotations of radar antenna and the interference attenuation resulting from frequency separation can substantially contribute to the link loss. Consequently, even in the scenario where cellular devices are fairly close to radar, there still will be periods of time when the link loss is high enough such that cellular systems can take opportunity to transmit while without interfering with radar. Numerical results show that in the scenario where spectrum sharing between a single cell and single rotating radar is considered, although with some interruptions, the communications system can achieve its data rate limit within a range that is a few kilometers away from the radar.