Aaron K. Shackelford

Spectral Nulling on Transmit via Nonlinear FM Radar Waveforms

Modern radars operate in electromagnetic environments crowded with other RF users. Adaptive spectral nulling on transmit can reduce interference from and to these other RF users. An analytical theory is developed for spectral nulling by a minimal adjustment, or offset, to the phase of the radar pulse that maintains constant pulse amplitude. Numerical examples show that a small time-varying phase offset designed by the proposed method can produce deep spectral nulls at one or more chosen frequencies in the radars spectral sidelobes with little other effect on the pulse spectrum or ambiguity function.

Partially Adaptive STAP using the FRACTA Algorithm

A partially adaptive space-time adaptive processor (STAP) utilizing the recently developed FRACTA algorithm is presented which significantly reduces the high computational complexity and large sample support requirements of fully adaptive STAP. Multi-window post-Doppler dimensionality reduction techniques are employed to transform the data prior to application of the FRACTA algorithm. The FRACTA algorithm is a reiterative censoring (RC) and detection algorithm which has been shown to provide excellent detection performance in nonhomogeneous interference environments. Two multi-window post-Doppler dimensionality reduction techniques are considered: PRI-staggered and adjacent-bin. The partially adaptive FRACTA algorithm is applied to the KASSPER I (knowledge-aided sensor signal processing & expert reasoning) challenge datacube. The pulse repetition interval (PRI)-staggered approach with D=6 filters per Doppler bin is found to provide the best detection performance, outperforming the fully adaptive case while simultaneously reducing the runtime by a factor of ten. Using this implementation, partially adaptive FRACTA detects 197 out of 268 targets with one false alarm. The clairvoyant processor (the covariance matrix for each range cell is known) detects 198 targets with one false alarm. In addition, the partially adaptive FRACTA algorithm is shown to be resilient to jamming, and performs well for reduced sample support situations. When compared with partially adaptive STAP using traditional sliding window processing (SWP), the runtime of partially adaptive FRACTA is 14 times faster, and the detection performance is significantly increased (SWP detects 46 out of 268 targets with one false alarm).

Doppler Compensation & Single Pulse Imaging using Adaptive Pulse Compression

The effects of target Doppler are addressed in relation to adaptive receive processing for radar pulse compression. To correct for Doppler-induced filter mismatch over a single pulse, the Doppler-compensated adaptive pulse compression (DC-APC) algorithm is presented whereby the respective Doppler shifts for large target returns are jointly estimated with the illuminated range profile and subsequently incorporated into the original APC adaptive receive filter formulation. As a result, the Doppler-mismatch-induced range sidelobes can be suppressed thereby regaining a significant portion of the sensitivity improvement that is possible when applying adaptive pulse compression (APC) without the existence of significant Doppler mismatch. In contrast, instead of compensating for Doppler mismatch, the single pulse imaging (SPI) algorithm generalizes the APC formulation for a bank of Doppler-shifted matched filters thereby producing a sidelobe-suppressed range-Doppler image from the return signal of a single radar pulse which is applicable for targets with substantial variation in Doppler. Both techniques are based on the recently proposed APC algorithm and its generalization, the multistatic adaptive pulse compression (MAPC) algorithm, which have been shown to be effective for the suppression of pulse compression range sidelobes thus dramatically increasing the sensitivity of pulse compression radar.

Time-Range Adaptive Processing for pulse agile radar

Some radar systems utilize pulse agility to mitigate interference or synthesize bandwidth. Transmitting different waveforms on a pulse-to-pulse basis can have deleterious effects when traditional pulse-Doppler processing is employed. In this paper a recursive MMSE-based receiver design, denoted as Time-Range Adaptive Processing, is presented. The new method jointly adapts in range and Doppler, thus yielding enhanced sensitivity when compared to adaptation in each dimension separately.

Thinned spectrum radar waveforms

Small phase perturbations applied to a stepped-frequency or linear-frequency-modulated radar waveform have been proposed as a means to generate frequency nulls in the spectrum of the transmitted waveform. By nulling selected frequencies (or thinning) in the spectrum of transmitted pulses, the interference between the transmitted and received signals is reduced, which facilitates the spectral cohabitation of multiple RF users. Preliminary experimental results of two methods of spectral nulling are presented with consideration to in-band and out-of-band interference. Range processing is examined to determine the effects of the phase perturbation on radar operations.

Space-Range Adaptive Processing for waveform-diverse radar imaging

Waveform-diverse radar arrays have been proposed as a method to facilitate single pulse imaging as well as to potentially enable simultaneous multi-mode operation. Transmitting different waveforms on the elements of a uniform linear array consequently raises the spatial and temporal sidelobes of the receiver matched filter. In this paper a recursive minimum mean square error based receiver design denoted as Space-Range Adaptive Processing is presented. The new method is capable of mitigating space range sidelobes thereby providing enhanced sensitivity for this transmission scheme.

Combined Multistatic Adaptive Pulse Compression and Adaptive Beamforming for Shared-Spectrum Radar

The recently proposed Multistatic Adaptive Pulse Compression (MAPC) algorithm has been shown to successfully suppress both range sidelobes and interference from multiple radars operating in the same spectrum, thus enabling shared-spectrum multistatic radar. In this paper, we present a method to increase the overall information capacity of the MAPC algorithm by performing joint adaptive pulse compression in conjunction with adaptive beamforming. The addition of an adaptive beamforming stage to the MAPC algorithm enables further mutual interference suppression and thus better estimation performance such that the number of multistatic radars simultaneously operating in the same spectrum may be increased for the same mean-square estimation error. Analysis of the performance of the adaptive beamforming MAPC algorithm in a variety of scenarios is presented. In addition, Monte Carlo analyses on the number of shared-spectrum radars are also presented

Shared-spectrum multistatic radar: Preliminary experimental results

In this paper we present preliminary experimental results demonstrating the ability of the multistatic adaptive pulse compression (MAPC) algorithm to suppress the mutual-interference generated by shared-spectrum radar signals, thus enabling shared-spectrum radar. The MAPC algorithm, a waveform diversity technique wherein multiple known transmitted waveforms are adaptively pulse compressed using reiterative minimum mean-square error (RMMSE) estimation, has been shown to successfully suppress both range sidelobes and interference from multiple radars operating in the same spectrum. In this paper, we present initial experimental results from the adaptive pulse compression (APC) test bed that demonstrate the ability of MAPC to mitigate both the mutual interference from multiple radars and pulse compression range sidelobes when applied to measured data.

Adaptive Pulse Compression: Preliminary Experimental Measurements

Preliminary experimental results from the adaptive pulse compression (APC) test bed are presented. A recently proposed adaptive processing technique has been shown via simulation to improve upon current pulse compression techniques through a process known as reiterative minimum mean-square error estimation (RMMSE). The RMMSE technique forms the basis of the APC and the Multistatic APC (MAPC) algorithms. In this paper, we present experimental results demonstrating the feasibility of these approaches. Several polyphase waveforms have been implemented in an experimental test bed. Initial results show that small non-linearities in the waveform generation process have only a marginal impact on the estimation performance of the algorithms. A discussion of the APC test bed followed by experimental results demonstrating the performances of the APC and MAPC algorithms are presented. These initial experimental results indicate that the APC approach is able to successfully mitigate pulse-compression sidelobes on measured data, and that the MAPC algorithm can successfully mitigate both the mutual-interference from shared-spectrum radar signals and pulse compression sidelobes on measured data.

A novel approach to shared-spectrum multistatic radar

In recent years the electromagnetic spectrum has become increasingly crowded due to the demand for higher bandwidths by both the radar and communications communities. One proposed solution to this issue is shared-spectrum multistatic radar, analogous to code-division multiple access (CDMA) communications. The recently proposed multistatic adaptive pulse compression (MAPC) algorithm has been shown to successfully suppress both range sidelobes and interference from multiple radars operating in the same spectrum, thus enabling shared-spectrum multistatic radar. In this paper, we present a method to increase the overall information capacity of the MAPC algorithm by performing joint adaptive pulse compression in conjunction with adaptive beamforming. The addition of an adaptive beamforming stage to the MAPC algorithm enables further mutual interference suppression and therefore better estimation performance such that the number of multistatic radars simultaneously operating in the same spectrum may be increased for the same mean-square estimation error. Analysis of the performance of the adaptive beamforming MAPC algorithm in the presence of Doppler mismatch is presented.