Ryan J. Riddolls

Canadian HF Over-the-Horizon Radar experiments using MIMO techniques to control auroral clutter

High frequency Over-the-Horizon Radar (OTHR) provides an economical means to track noncooperative air targets over large expanses of land and ocean. However, early attempts to run OTHR in Canada in the 1970s were confounded by the presence of intense radar clutter originating in the auroral zone. Recent advances in Multiple-Input Multiple-Output (MIMO) OTHR technology, namely orthogonal waveform transmit arrays and fully sampled receive arrays, provide an opportunity to revisit the possibility of OTHR in Canada. An OTHR testbed has been built in Ottawa, Canada to determine the capabilities of the technology. The testbed consists of a MIMO OTHR with 4 transmit channels and 4 receive channels. Some preliminary data show that MIMO processing is effective in suppressing the clutter. It is then proposed to upgrade the testbed to a larger-scale system.

Limits on the detection of low-Doppler targets by a High Frequency hybrid sky-surface wave radar system

A high frequency (HF) radar system comprising a skywave transmit channel and surface wave receive channel is studied. Simple analytic expressions for the resolution of this radar system are determined by considering the spreading of radar signals in Doppler and angle during the ionospheric propagation. The detection of ocean surface targets within the patch of ocean surface illuminated by the radar beam is then determined by comparing the radar cross section of the ocean patch with typical vessel radar cross sections. It is shown that a hybrid sky-surface wave radar can detect low-Doppler ships down to 30 dBm2 cross section during the day and down to 40 dBm2 at night, during calm ionospheric conditions. During periods of spread F ionospheric turbulence, where the temporal correlation time decreases by an order of magnitude, the corresponding vessel detection capability decreases by two orders of magnitude.

Ionospheric and auroral clutter models for HF surface wave and over-the-horizon radar systems

[1] The detection performance of high frequency surface wave radar (HFSWR) and high frequency over-the-horizon radar (OTHR) systems is heavily influenced by the presence of radar clutter. In HFSWR systems, the clutter has its origins in vertical-incidence ionospheric reflections, whereas in OTHR systems, the origin is Bragg backscatter from plasma structures in the auroral zone. This paper models the spreading of the radar clutter signal in the Doppler and angle-of-arrival domains that arises from forward-scattering effects as the radar pulse propagates through regions of ionospheric plasma irregularities. The models use a geometric optics approach to determine the power spectrum of the radar signal phase. This power spectrum is then used to simulate three-dimensional space-time-range radar data cubes. The accuracy of the models is tested by comparing the simulated data to measured data cubes. As an application, the data are then used to evaluate the performance of the newly developed fast fully adaptive (FFA) space-time adaptive processing (STAP) scheme to improve the extraction of target echoes from a clutter background.

Fast fully adaptive processing: A multistage STAP approach

Due to the need for adequate statistically homogeneous training, full-dimensional space-time adaptive processing (STAP) is well accepted to be impractical. Several previous works have addressed this issue by reducing the adaptive degrees of freedom (DoF), in turn reducing the required training. In this paper, we introduce a new multistage STAP approach that significantly reduces the required sample support while still processing all available DoF. The multistage fast fully adaptive (FFA) scheme draws inspiration from the butterfly structure of the fast Fourier transform. It uses a “divide-and-conquer” approach by creating several smaller STAP problems but then combines the outputs of each problem adaptively as well. The reduction in required sample support rivals currently available reduced DoF algorithms. We also develop three variants of the algorithm, including one that uses random subdivisions of the original STAP problem.We test the efficacy of the algorithms developed via simulations based on simulated airborne radar data and measured high-frequency surface wave radar data. The results show that for simulated homogeneous data, the performance of the FFA approaches is comparable to that of available STAP algorithms; however, with measured data, the FFA approach provides significantly better performance.

Joint waveform optimization and adaptive processing for random phase radar signals

We consider waveform design for multiple-input, multiple-output radar systems for the case where the signal, during propagation, undergoes phase perturbations. We formulate an iterative algorithm to obtain both waveform parameters and the weights of the adaptive matched filter. An example of a clutter and target model is provided to show how the optimal waveform design improves the detection performance of a random-phase radar compared to traditional waveforms.

MIMO fast fully adaptive processing in Over-the-Horizon Radar

High frequency Over-the-Horizon Radar (OTHR) provides an economical means to track noncooperative air targets over large expanses of land and ocean. However, OTHR in Canada is confounded by the presence of radar clutter from the region of the aurora borealis. Given the time-varying nature of auroral clutter, this paper proposes joint adaptive transmit and receive beamforming as a key tool to deal with this clutter. This beamforming is an alternative adaptive process based on the previously proposed fast-fully adaptive (FFA) scheme extended to couple transmit and receive beamforming, specifically for slow-time multiple-input multiple-output (MIMO) radar. We test the efficacy of this algorithm using measured OTHR data.

Two-dimensional adaptive processing for ionospheric clutter mitigation in High Frequency Surface Wave Radar

High Frequency Surface Wave Radar (HFSWR) is a technology used for over-the-horizon detection of ocean vessels. This radar exploits the diffraction of electromagnetic waves around the curved surface of the Earth. To minimize the attenuation of the diffracted waves, the radar must operate at frequencies in the lower part of the high frequency (HF) band. However, radar signals at these frequencies also reflect from the Earths ionosphere, which leads to radar clutter at ranges beyond 200 km. The linear broadside receive arrays used by conventional HFSWR systems cannot filter out this clutter as the arrays do not have any resolving power in elevation angle. Reported here are experimental investigations of the clutter suppression capability of one- and two-dimensional HFSWR adaptive processors. Three configurations are compared: one-dimensional spatial adaptive processing, two-dimensional spatial adaptive processing, and space-time adaptive processing. In all cases the number of adaptive degrees of freedom is 16. It is found that the best results are achieved by two-dimensional spatial adaptive processing, where a processing gain of up to about 20 dB can be achieved.

Joint waveform optimization and adaptive processing for random-phase radar signals

We consider waveform design for multiple-input, multiple-output radar systems for the case where the signal, during propagation, undergoes phase perturbations. We formulate an iterative algorithm to obtain both waveform parameters and the weights of the adaptive matched filter. An example of a clutter and target model is provided to show how the optimal waveform design improves the detection performance of a random-phase radar compared to traditional waveforms.

Joint transmit-receive adaptive beamforming experimental results from an auroral-zone Canadian over-the-horizon radar system

New data is presented from an over-the-horizon radar experiment featuring simultaneous multiple transmit channels and multiple receive channels. A joint transmit-receive adaptive beamformer is demonstrated, whereby nulls are placed in the direction of auroral clutter echoes on both transmit and receive. It is shown that the level of the clutter suppression produced by the joint transmit-receive beamformer is the multiplicative product of separate adaptive beamformers on transmit and receive, in accordance with theoretical predictions. The adaptive joint transmit-receive beamformer demonstrates a powerful technique for controlling auroral ionospheric clutter for an over-the-horizon radar airspace surveillance mission.

Music-Enhanced CFAR for High Frequency Over-the-Horizon Radar

To increase the number of location options for an HF surface-wave radar (HFSWR) there is significant interest in reducing the physical size of the receive array. Reducing the aperture results in a degradation of both sensitivity and azimuth information. Azimuth accuracy may be retained by the use of high-resolution methods (such as MUSIC) that have a significantly smaller beamwidth than standard beamforming. It is expected that the application of these high-resolution methods will help retain azimuth information with reduced aperture size. This paper evaluates the effects of reducing the physical aperture of the linear receive array used in HFSWR and using post-detection azimuth re-estimation by high-resolution methods to maintain azimuth resolution, accuracy, and hence tracking performance. This paper is limited to evaluating the effect of increased azimuth beamwidth and does not address the issue of reduced radar sensitivity. Data for the evaluation was obtained from an HFSWR system located at Cape Race, Newfoundland, Canada. The accuracy of the detection centroid for a full 16-element array is compared to the accuracy for a half-aperture 8-element array. It is shown that similar accuracy can be achieved from the shortened array employing the MUSIC-Enhanced CFAR compared to the full size array using the conventional CFAR processing.