B. Steinberg

Bio: B. Steinberg is an academic researcher from United States Naval Research Laboratory. The author has contributed to research in topics: Radar imaging & Distortion. The author has an hindex of 1, co-authored 1 publications receiving 87 citations.

Radar imaging from a distorted array: The radio camera algorithm and experiments

Abstract: High angular resolution radar imaging may be achieved with a large-aperture antenna even if the aperture is distorted, provided that adaptive signal processing compensates for the distortion. The radio camera is an instrument designed for this purpose. Its algorithm for imaging ground-based targets is described and experimental results are given for a 3 cm wavelength demonstration system using a distorted 27-m random sparse array. The measured beamwidth of 1 mrad conformed to theory, confirming the validity of the technique. Extension of the algorithm to accommodate isolated targets such as aircraft and ships also is discussed.

Weighted least-squares estimation of phase errors for SAR/ISAR autofocus

Abstract: A new method of phase error estimation that utilizes the weighted least-squares (WLS) algorithm is presented for synthetic aperture radar (SAR)/inverse SAR (ISAR) autofocus applications. The method does not require that the signal in each range bin be of a certain distribution model, and thus it is robust for many kinds of scene content. The most attractive attribute of the new method is that it can be used to estimate all kinds of phase errors, no matter whether they are of low order, high order, or random. Compared with other methods, the WLS estimation is optimal in the sense that it has the minimum variance of the estimation error. Excellent results have been obtained in autofocusing and imaging experiments on real SAR and ISAR data.

Microwave imaging of aircraft

Abstract: Three methods of imaging aircraft from the ground with microwave radar with quality suitable for aircraft target recognition are described. The imaging methods are based on a self-calibration procedure called adaptive beamforming that compensates for the severe geometric distortion inherent in any imaging system that is large enough to achieve the high angular resolution necessary for two-dimensional target imaging. The signal processing algorithm is described and X-band (3-cm)-wavelength experiments demonstrate its success on commercial aircraft flying into Philadelphia International Airport. >

Radar Coincidence Imaging: an Instantaneous Imaging Technique With Stochastic Signals

Abstract: Motivated by classical coincidence imaging which has been realized in optical systems, an instantaneous microwave-radar imaging technique is proposed to obtain focused high-resolution images of targets without motion limitation. Such a radar coincidence imaging method resolves target scatterers based on measuring the independent waveforms of their echoes, which is quite different from conventional radar imaging techniques where target images are derived depending on time-delay and Doppler analysis. Due to the peculiar features of coincidence imaging, there are two potential advantages of the proposed imaging method over the conventional ones: 1) shortening the imaging time to even a pulse width without resolution deterioration so as to improve the performance of processing noncooperative targets and 2) simplifying the receiver complexity, resulting in a lower cost and platform flexibility in application. The basic principle of radar coincidence imaging is to employ the time-space independent detecting signals, which are produced by a multitransmitter configuration, to make scatterers located at different positions reflect independent waveforms from each other, and then to derive the target image based on the prior knowledge of this detecting signal spatial distribution. By constructing the mathematic model, the necessary conditions of the transmitting waveforms are analyzed for achieving radar coincidence imaging. A parameterized image-reconstruction algorithm is introduced to obtain high resolution for microwave radar systems. The effectiveness of this proposed imaging method is demonstrated via a set of simulations. Furthermore, the impacts of modeling error, noise, and waveform independence on the imaging performance are discussed in the experiments.

Moving target imaging and trajectory computation using ISAR

Abstract: Novel algorithms for moving target imaging and trajectory computation using a two-receiver radar are presented. The range-bin alignment is implemented with an adaptive method using the envelope correlation feature of different returns and the angular trajectory equation is solved using a linear least squares method combined with a unique phase-unwrapping technique. The angular positions of the synthetic array elements are determined from the trajectory computation. Three target models moving along a perturbed straight line are used to verify the proposed algorithms. >

Self-cohering large antenna arrays using the spatial correlation properties of radar clutter

Abstract: A technique for self-calibrating a large antenna array system in the absence of a beamforming point source is presented that uses the spatial correlation properties of radar clutter. The array could be real or synthetic. It is shown that if R(X), the spatial autocorrelation function of the field (as measured by adjacent element pairs), is ensured to be real and positive in the neighborhood of the origin, both periodic and aperiodic arrays can be synchronized, forming retrodirective beams pointing at the axis of symmetry of the radar transmitter, provided that the interelement spacing does not exceed some limit (the order of the size of the transmitting aperture). If the spatial autocorrelation function is complex but has a linear phase, it is shown that one can still synchronize both periodic and aperiodic arrays, while if the phase of R(X) is nonlinear, only periodic arrays can be synchronized. In both cases of complex R(X), a residual beam-pointing error occurs. Computer simulations and airborne sea clutter data are reported that verify the theory and practicality of the algorithm. >