Shannon D. Blunt

Adaptive pulse compression via MMSE estimation

Radar pulse compression involves the extraction of an estimate of the range profile illuminated by a radar in the presence of noise. A problem inherent to pulse compression is the masking of small targets by large nearby targets due to the range sidelobes that result from standard matched filtering. This paper presents a new approach based upon a minimum mean-square error (MMSE) formulation in which the pulse compression filter for each individual range cell is adaptively estimated from the received signal in order to mitigate the masking interference resulting from matched filtering in the vicinity of large targets. The proposed method is compared with the standard matched filter and least-squares (LS) estimation and is shown to be superior over a variety of stressing scenarios.

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.

Intrapulse Radar-Embedded Communications

The embedding of a covert communication signal amongst the ambient scattering from an incident radar pulse has previously been achieved by modulating a Doppler-like phase shift sequence over numerous pulses (i.e., on an inter-pulse basis). In contrast, this paper considers radar-embedded communications on an intrapulse basis whereby an incident radar waveform is converted into one of K communication waveforms, each of which acts as a communication symbol representing some predetermined information (e.g., a bit sequence). To preserve a low intercept probability, this manner of radar-embedded communications necessitates prudent selection of the set of communication waveforms as well as interference cancellation on receive. A general mathematical model and subsequent optimization problem is established for the design of the communication waveforms, from which three design strategies are developed. Also, receiver design issues are discussed, and an interference-canceling maximum likelihood receiver is presented. Performance results are presented in terms of the communication symbol error rate as well as a correlation-based metric from which intercept probability can be inferred. It is demonstrated that, given persistent radar illumination with a pulse repetition frequency (PRF) of 1-2 kHz, intrapulse radar-embedded communications can theoretically achieve data-rates commensurate with speech coding (for the interval of the radar dwell time) with the potential for even higher data-rates if additional diversity is appropriately incorporated.

Challenge problems in spectrum engineering and waveform diversity

We describe and discuss some of the current challenges facing radar that result from continued spectral encroachment, which necessitating enhanced robustness to interference, agile waveform-diverse operation, and greater synergy between the signal processing and the physical radar/environment. Subsequently, specific research topics are suggested in which spectrum engineering and waveform diversity may yield viable solutions. In so doing, this paper also provides an introduction to the special session on radar spectrum engineering and waveform diversity affiliated with NATO Task Groups SET-182 and SET-179, respectively.

Analysis of range-angle coupled beamforming with frequency-diverse chirps

Recently range-dependent (or time-varying) beamforming has been presented as a method to spread transmit energy over a desired spatial extent via a linear frequency shift across the waveforms transmitted at each element of an array. This element-level waveform diversity yields additional degrees of freedom relative to traditional beamforming techniques for which some sensing benefits have been suggested. In this paper, chirp waveforms with slightly different starting frequencies are analyzed to characterize the associated range-dependent beampattern. Specifically, it is determined that by utilizing this particular waveform structure, the energy transmitted over a pulse duration can be spread in a practically linear manner within the spatial extent specified by two angles despite the nonlinear relationship between spatial and electrical angles if the set of frequency-diverse chirps are appropriately parameterized. Additionally, a space-range ambiguity diagram is formulated. The ambiguity is discussed for the traditional and frequency-diverse array scenarios.

Polyphase-coded FM (PCFM) radar waveforms, part II: optimization

This paper addresses polyphase code optimization with respect to the nonlinear frequency modulation waveform generated by the continuous phase modulation implementation. A greedy search leveraging the complementary metrics of peak sidelobe level, integrated sidelobe level, and spectral content yield extremely low range sidelobes relative to waveform time-bandwidth product. Transmitter distortion is also incorporated into the optimization via modeling and actual hardware. Thus the physical radar emission can be designed to address spectrum management and enable the physical realization of advanced waveform-diverse schemes.

Embedding information into radar emissions via waveform implementation

In this paper an approach for the joint design of multiple receive filters is described that enables the use of different waveforms during a radar CPI while minimizing the attendant Doppler coherency degradation due to range sidelobe clutter modulation. This capability allows for a set of unique radar waveforms to serve the dual purpose of acting as communication symbols while acceptable radar performance is maintained. The receive filter design approach is based upon the well-known Least-Squares (LS) mismatch filter formulation. The novel modification is the iterative adaptation of the desired response such that all the waveform/filter pair responses are driven to be identical.

Stap using knowledge-aided covariance estimation and the fracta algorithm

In the airborne space-time adaptive processing (STAP) setting, a priori information via knowledge-aided covariance estimation (KACE) is employed in order to reduce the required sample support for application to heterogeneous clutter scenarios. The enhanced FRACTA (FRACTA.E) algorithm with KACE as well as Doppler-sensitive adaptive coherence estimation (DS-ACE) is applied to the KASSPER I & II data sets where it is shown via simulation that near-clairvoyant detection performance is maintained with as little as 1/3 of the normally required number of training data samples. The KASSPER I & II data sets are simulated high-fidelity heterogeneous clutter scenarios which possess several groups of dense targets. KACE provides a priori information about the clutter covariance matrix by exploiting approximately known operating parameters about the radar platform such as pulse repetition frequency (PRF), crab angle, and platform velocity. In addition, the DS-ACE detector is presented which provides greater robustness for low sample support by mitigating false alarms from undernulled clutter near the clutter ridge while maintaining sufficient sensitivity away from the clutter ridge to enable effective target detection performance

Spatio–Temporal Reconstruction of Bilateral Auditory Steady-State Responses Using MEG Beamformers

A rapidly growing number of neuromagnetic studies focus on the analysis of auditory steady-state responses (ASSR) in relation to a diverse array of factors including age, selective attention, and presence of psychopathology. The objectives of these studies require accurate spatio-temporal estimation of the underlying neural generators, a challenging task due to the relatively low signal strength and high correlation between bilateral auditory cortical sources. This paper evaluates the performance of two beamforming schemes that can potentially overcome such difficulties: 1) the linearly constrained minimum variance beamformer with partial sensor coverage (LCMV-PSC), and 2) the multiple constrained minimum-variance beamformer with coherent source region suppression (MCMV-CSRS). Simulation experiments are conducted to assess the impact of source parameters on the reconstruction accuracy. The results indicate that the LCMV-PSC method is prone to localization errors that essentially occur along medio-lateral directions, increase with source depth, and are associated to amplitude and phase distortions of the estimated time courses of activity. Comparatively, the MCMV-CSRS method exhibits precise localization and minimal amplitude and phase distortion for a broad range of relative interferers positions within the suppression region. The results from the numerical experiments are validated on real magnetoencephalographic (MEG) data collected from a 40-Hz ASSR paradigm.

Multistatic adaptive pulse compression

A new technique denoted as multistatic adaptive pulse compression (MAPC) is introduced which exploits recent work on adaptive pulse compression (APC) in order to jointly separate and pulse compress the concurrently received return signals from K proximate multistatic radars operating (i.e., transmitting) within the same spectrum. For the return signal from a single pulse of a monostatic radar, APC estimates the particular receive filter for a given range cell in a Bayesian sense reiteratively by employing the matched filter estimates of the surrounding range cell values as a priori knowledge in order to place temporal (i.e., range) nulls at the relative ranges occupied by large targets and thereby suppress range sidelobes to the level of the noise. The MAPC approach generalizes the APC concept by jointly estimating the particular receive filter for each range cell associated with each of several concurrently-received radar return signals occupying the same spectrum. As such, MAPC is found to enable shared-spectrum multistatic operation and is shown to yield substantial performance improvement in the presence of multiple spectrum-sharing radars as compared with both standard matched filters and standard least-squares mismatched filters