In this paper we introduce multi-channel techniques to compensate for effects of antenna shading and crosstalk in wideband, wide-angle full polarization radar imaging. We model the systems as a 2D integral operator that includes the transmit pulse function, receive and transmit antenna transfer functions, and response from scattering objects. Existing imaging algorithms provide an approximate inversion of this integral operator, without compensation for the effect of antenna transfer functions. Thus, standard processing results in image quality diminished by the inherent variation of the antenna response--in magnitude, phase and polarization--across a large band of frequencies and wide range of aspect angles. We propose three inversion techniques for this integral operator, to improve polarization purity and to achieve localized point spread functions. The first technique uses a local approximation to the system model, and propose a conceptually simple method for the inversion. The other two techniques propose inversion methods for the exact system model in different transform domains. The result is imagery with improved polarization purity and a more localized point spread function.
A new, fast algorithm for synthetic aperture radar (SAR) image formation is introduced. The algorithm is based on a decomposition of the time domain backprojection technique. It inherits the primary advantages of time domain backprojection: simple motion compensation, simple and spatially unconstrained propagation velocity compensation, and localized processing artifacts. The computational savings are achieved by using a divide-and-conquer strategy of decomposition, and exploiting spatial redundancy in the resulting sub-problems. The decomposition results in a quadtree data structure that is readily parallelizable and requires only limited interprocessor communications. For a SAR with N aperture points and an N by N image area, the algorithm is seen to achieve O(N<SUP>2</SUP>logN) complexity. The algorithm allows a direct trade between processing speed and focused image quality.
We present an algorithm for the removal of narrow-band interference from wideband signals. We apply the algorithm to suppress radio frequency interference encountered by ultra- wideband synthetic aperture radar systems used for foliage- and ground-penetrating imaging. For this application, we seek maximal reduction of interference energy, minimal loss and distortion of wideband target responses, and real-time implementation. To balance these competing objectives, we exploit prior information concerning the interference environment in designing an estimate-and-subtract-estimation algorithm. The use of prior knowledge allows fast, near-least-squares estimation of the interference and permits iterative target signature excision in the interference estimation procedure to decrease estimation bias. The results is greater interference suppression, less target signature loss and distortion, and faster computation than is provided by existing techniques.
This paper describes a computationally efficient, high-performance, UWB radar interference suppression algorithm. An adaptive FIR (finite impulse response) prediction-error noise- whitening filter exhibits minimal computational complexity and achieves 30 dB interference reduction per pulse (1 microsecond(s) long) with 16-bit simulated interference. Using measured interference data digitized to 8-bits with a 6.5 effective bit digitizer, collected just north of Washington, DC at the Army Research Laboratory, the technique achieved 20 to 27 dB of reduction. To minimize the computational load, the filter weights are periodically determined from data collected during a fraction of a radar range sweep. These weights are found to be effective for hundreds of subsequent radar pulses. Previous work on an estimate-and-subtract, tone-extraction technique resulted in 20 dB average interference reduction on the same measured data with a computational load linearly related to the number of tones extracted. The adaptive filtering approach uses an over-determined system producing an FIR filter with N taps, independent of the number of interference signals. An iterative technique to reduce the range sidelobes caused by the filter's impulse response is also presented. The computational load of this iterative stage is, at worst, linearly related to the number of targets whose sidelobes are extracted. It is shown that, with a small reduction in performance, the sidelobe reduction can be accomplished with a relatively small increase in the overall computational load. The computational complexity of the proposed technique relative to the estimate-and- subtract technique depends on the signal and interference environment and on the acceptable sidelobe level. A comprehensive radio and TV interference simulator was developed to test the interference suppression algorithm. It avoids difficulties in memory requirements and code complexity typically encountered in high-sample rate, long duration, and UWB simulations. Data was generated for various population densities, sampling rates, and quantization levels. Results using the simulation data showed that the performance of the algorithm was related to the quantization level with more bits producing better results.
The U.S. Army is interested in demonstrating a capability of detecting and discriminating tactical targets concealed in foliage. To investigate foliage and ground penetration phenomena, a fully polarimetric laboratory Synthetic Aperture Radar system has been built on a rooftop rail. The system uses impulse technology covering a bandwidth of 40 MHz to 1 GHz. The first image from the system showed the -3 db beamwidths to be 5 inches in range and 11 inches in cross-range measured to an 8-ft triangular plate corner reflector. This paper will briefly describe the measurement system and present images made of canonical targets in winter foliage.