An Approach to Active Sensor Imaging

In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is obtained by considering a novel range and scanning angle plane different from the conventional methods. An alternative method is briefly proposed for smoothing the target density function by taking advantage of Walsh functions. Although the imaging is obtained via the phased array radars, the problem associated with beamforming in linear phased array radar system is bypassed in this new algorithm

The Case for Combining a Large Low-Band Very High Frequency Transmitter With Multiple Receiving Arrays for Geospace Research: A Geospace Radar

We argue that combining a high‐power, large‐aperture radar transmitter with several large‐aperture receiving arrays to make a geospace radar—a radar capable of probing near‐Earth space from the upper troposphere through to the solar corona—would transform geospace research. We review the emergence of incoherent scatter radar in the 1960s as an agent that unified early, pioneering research in geospace in a common theoretical, experimental, and instrumental framework, and we suggest that a geospace radar would have a similar effect on future developments in space weather research. We then discuss recent developments in radio‐array technology that could be exploited in the development of a geospace radar with new or substantially improved capabilities compared to the radars in use presently. A number of applications for a geospace radar with the new and improved capabilities are reviewed including studies of meteor echoes, mesospheric and stratospheric turbulence, ionospheric flows, plasmaspheric and ionospheric irregularities, and reflection from the solar corona and coronal mass ejections. We conclude with a summary of technical requirements

ADAM: a general method for using various data types in asteroid reconstruction

We introduce ADAM, the All-Data Asteroid Modelling algorithm. ADAM is simple and universal since it handles all disk-resolved data types (adaptive optics or other images, interferometry, and range-Doppler radar data) in a uniform manner via the 2D Fourier transform, enabling fast convergence in model optimization. The resolved data can be combined with disk-integrated data (photometry). In the reconstruction process, the difference between each data type is only a few code lines defining the particular generalized projection from 3D onto a 2D image plane. Occultation timings can be included as sparse silhouettes, and thermal infrared data are efficiently handled with an approximate algorithm that is sufficient in practice due to the dominance of the high-contrast (boundary) pixels over the low-contrast (interior) ones. This is of particular importance to the raw ALMA data that can be directly handled by ADAM without having to construct the standard image. We study the reliability of the inversion by using the independent shape supports of function series and control-point surfaces. When other data are lacking, one can carry out fast nonconvex lightcurve-only inversion, but any shape models resulting from it should only be taken as illustrative global-scale ones.Comment: 11 pages, submitted to A&

Surface roughness measuring system

Significant height information of ocean waves, or peaks of rough terrain is obtained by compressing the radar signal over different widths of the available chirp or Doppler bandwidths, and cross-correlating one of these images with each of the others. Upon plotting a fixed (e.g., zero) component of the cross-correlation values as the spacing is increased over some empirically determined range, the system is calibrated. To measure height with the system, a spacing value is selected and a cross-correlation value is determined between two intensity images at a selected frequency spacing. The measured height is the slope of the cross-correlation value used. Both electronic and optical radar signal data compressors and cross-correlations are disclosed for implementation of the system

Vegetation analysis with radar imagery

Vegetation maps prepared from radar imagery obtained over several climatic environment

Asteroid Models from Multiple Data Sources

In the past decade, hundreds of asteroid shape models have been derived using the lightcurve inversion method. At the same time, a new framework of 3-D shape modeling based on the combined analysis of widely different data sources such as optical lightcurves, disk-resolved images, stellar occultation timings, mid-infrared thermal radiometry, optical interferometry, and radar delay-Doppler data, has been developed. This multi-data approach allows the determination of most of the physical and surface properties of asteroids in a single, coherent inversion, with spectacular results. We review the main results of asteroid lightcurve inversion and also recent advances in multi-data modeling. We show that models based on remote sensing data were confirmed by spacecraft encounters with asteroids, and we discuss how the multiplication of highly detailed 3-D models will help to refine our general knowledge of the asteroid population. The physical and surface properties of asteroids, i.e., their spin, 3-D shape, density, thermal inertia, surface roughness, are among the least known of all asteroid properties. Apart for the albedo and diameter, we have access to the whole picture for only a few hundreds of asteroids. These quantities are nevertheless very important to understand as they affect the non-gravitational Yarkovsky effect responsible for meteorite delivery to Earth, or the bulk composition and internal structure of asteroids.Comment: chapter that will appear in a Space Science Series book Asteroids I

Compressed Sensing Applied to Weather Radar

We propose an innovative meteorological radar, which uses reduced number of spatiotemporal samples without compromising the accuracy of target information. Our approach extends recent research on compressed sensing (CS) for radar remote sensing of hard point scatterers to volumetric targets. The previously published CS-based radar techniques are not applicable for sampling weather since the precipitation echoes lack sparsity in both range-time and Doppler domains. We propose an alternative approach by adopting the latest advances in matrix completion algorithms to demonstrate the sparse sensing of weather echoes. We use Iowa X-band Polarimetric (XPOL) radar data to test and illustrate our algorithms.Comment: 4 pages, 5 figrue