Russell D. Brown

A deterministic least-squares approach to space-time adaptive processing (STAP)

A direct data domain (D/sup 3/) least-squares space-time adaptive processing (STAP) approach is presented for adaptively enhancing signals in a nonhomogeneous environment. The nonhomogeneous environment may consist of nonstationary clutter and could include blinking jammers. The D/sup 3/ approach is applied to data collected by an antenna array utilizing space and in time (Doppler) diversity. Conventional STAP generally utilizes statistical methodologies based on estimating a covariance matrix of the interference using data from secondary range cells. As the results are derived from ensemble averages, one filter (optimum in a probabilistic sense) is obtained for the operational environment, assumed to be wide sense stationary. However for highly transient and inhomogeneous environments the conventional statistical methodology is difficult to apply. Hence, the D/sup 3/ method is presented as it analyzes the data in space and time over each range cell separately. The D/sup 3/ method is deterministic in approach. From an operational standpoint, an optimum method could be a combination of these two diverse methodologies. This paper represents several new D/sup 3/ approaches. One is based on the computation of a generalized eigenvalue for the signal strength and the others are based on the solution of a set of block Hankel matrix equations. Since the matrix of the system of equations to be solved has a block Hankel structure, the conjugate gradient method and the fast Fourier transform (FFT) can be utilized for efficient solution of the adaptive problem. Illustrative examples presented in this paper use measured data from the multichannel airborne radar measurements (MCARM) database to detect a Sabreliner in the presence of urban, land, and sea clutter. An added advantage for the D/sup 3/ method in solving real-life problems is that simultaneously many realizations can be obtained for the same solution for the signal of interest (SOI). The degree of variability amongst the different results can provide a confidence level of the processed results. The D/sup 3/ method may also be used for mobile communications.

Assessment of multichannel airborne radar measurements for analysis and design of space-time processing architectures and algorithms

System design studies and detailed radar simulations have identified the utility of space-time adaptive processing (STAP) to accomplish target detection in cases where the target Doppler is immersed in sidelobe clutter and jamming. A recent US Air Force investment in STAP has produced a database of multichannel airborne data, through Rome Laboratorys Multichannel Airborne Radar Measurement (MCARM) program, to further develop STAP architectures and algorithms suited to operational environments. An aspect of actual data not typically incorporated into simulation scenarios is the nonhomogeneous features of real-world clutter and interference scenarios. In this paper we investigate the impact of nonhomogeneous data on the performance of STAP. Furthermore, we propose a preliminary scheme to detect and excise nonhomogeneous secondary data in the sample covariance estimation, thereby dramatically improving STAP performance as shown through a specific example using monostatic MCARM data.

Expert System Constant False Alarm Rate (CFAR) Processor

The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.

Artificial intelligence applications to constant false alarm rate (CFAR) processing

False alarms are a significant problem in wide area surveillance radar. Many different constant false alarm rate (CFAR) algorithms have been developed to effectively deal with the various types of backgrounds that are encountered. However, any single algorithm is likely to be inadequate in a dynamically changing environment. The approach suggested is to intelligently select the CFAR algorithm or algorithms being executed at any given time, based upon the observed characteristics of the environment. This approach requires sensing the environment, employing the most suitable CFAR algorithm(s), and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.<<ETX>>

STAP for clutter suppression with sum and difference beams

A unique approach for airborne radar clutter rejection is developed and evaluated. This spatial and temporal adaptive approach employs the sum and difference beams of an antenna, which has significant practical advantages because it can be implemented with no/little change to the front-end electronics of airborne systems where sum and difference beams already exist for other reasons. The low sidelobe implementation of many sum and difference beam systems and the low gain of the difference beam in the direction of the target gives this approach the potential in many radars for a more predictable response pattern. The impact of these factors is shown in an airborne clutter rejection demonstration where the performance of this approach is compared with that of the factored approach (FA) using additional spatial channels and that of conventional pulse-Doppler (PD) processing. Reliable detection of an injected target is only achieved by this approach.

A space-time adaptive processing approach for improved performance and affordability

A space-time adaptive processing (STAP) method is described which uses only the mainbeam or sum (/spl Sigma/) and difference (/spl Delta/) channels of a airborne radar for adaptive suppression of clutter in the joint angle-Doppler domain. This method, called /spl Sigma//spl Delta/-STAP, dramatically reduces system implementation cost, as it requires only two digitized channels, and is applicable as an upgrade to both phased array and continuous aperture airborne radar systems. It is shown that /spl Sigma//spl Delta/-STAP offers near optimal performance and requires much smaller sample support than other approaches, which is critical for successful operation in severely nonhomogeneous clutter.

Near field focusing algorithm for high frequency ground penetration imaging radar

Ground penetrating radar has been successfully used for imaging stratigraphic structures. The goal of our ground penetrating radar program is to provide a capability for strategic subsurface target detection for military applications. This paper describes an experimental approach to high frequency (HF) radar sub-surface profiling, and the results obtained from signal and data processing for deep tunnel detection. Ongoing experiments employ a bistatic radar system designed to detect buried objects located in the near field of the HF sensor. Data analysis requires the use of synthetic aperture radar (SAR) processing to focus the image. Currently, experiments are conducted using surface contact antennas as part of a larger effort with an ultimate goal of collecting data via airborne sensors. The immediate goal of this effort is to determine the resolution achievable at depths commensurate with buried structures of strategic importance. This paper also examines the trade-off between frequency and propagation in an attempt to effect the best resolution possible.

An improved and affordable space-time adaptive processing approach

A space-time adaptive processing (STAP) method is described which uses only the main-beam or sum (/spl Sigma/) and difference (/spl Delta/) channels of an airborne radar for adaptive suppression of clutter in the joint angle-Doppler domain. This method, called /spl Sigma//spl Delta/-STAP, dramatically reduces system implementation cost, as it requires only two digitized channels, and is also applicable as an upgrade to both phased array and continuous aperture airborne radar systems. It is shown that /spl Sigma//spl Delta/-STAP offers near optimal performance and requires much smaller sample support than other approaches, which is critical for successful operation in severely nonhomogeneous clutter. Other advantages of /spl Sigma//spl Delta/-STAP identified include significantly simplified system calibration and well-behaved response patterns.

Design, implementation and evaluation of parallel pipelined STAP on parallel computers

Performance results are presented for the design and implementation of parallel pipelined space-time adaptive processing (STAP) algorithms on parallel computers. In particular, the issues involved in parallelization, our approach to parallelization, and performance results on an Intel Paragon are described. The process of developing software for such an application on parallel computers when latency and throughput are both considered together is discussed and tradeoffs considered with respect to inter and intratask communication and data redistribution are presented. The results show that not only scalable performance was achieved for individual component tasks of STAP but linear speedups were obtained for the integrated task performance, both for latency as well as throughput. Results are presented for up to 236 compute nodes (limited by the machine size available to us). Another interesting observation made from the implementation results is that performance improvement due to the assignment of additional processors to one task can improve the performance of other tasks without any increase in the number of processors assigned to them. Normally, this cannot be predicted by theoretical analysis.

Bistatic radar denial/embedded communications via waveform diversity

Use of an interferometer along with a host radar is proposed for simultaneously achieving coherent reference denial and embedded communications. To prevent self-jamming, spatial orthogonality is achieved between the interferometer antenna pattern and main beam of the host radar. Costas and orthogonal frequency division multiplexing (OFDM) signals are suggested for the host radar and interferometer, respectively. The effectiveness of the interferometer masking signal on a non-cooperative bistatic radar is discussed.