This article introduces the experiment design for Moon imaging based on Sanya incoherent scatter radar (SYISR) and algorithm research in data processing. The peak power of SYISR is 2 MW. The transmitted frequency used for Moon imaging experiments is 430 MHz. We conducted Moon imaging experiments using two types of waveforms, 13-bit Barker code, and linear frequency modulation (LFM) chirp. Considering both resolution and signal-to-noise ratio (SNR), the use of an LFM chirp with a bandwidth of 0.3 MHz and a pulsewidth of 2 ms can give higher SNR and resolution for Moon imaging using SYISR. Several key techniques were applied in the experiment design and data processing: 1) for the reliability of the imaging algorithm, the range-Doppler imaging algorithm commonly used in synthetic aperture imaging was applied; 2) to avoid the sidelobe effect of the 13-bit Barker code matched filter, a sidelobe-free filter was used; and 3) to mitigate the problem of “north–south ambiguity,” mosaic imaging of the Doppler northern and southern hemispheres of the nearside of the Moon was adopted. Two types of imaging results are obtained: mosaic images of the northern and southern hemispheres of the Moon and local regional images. The results demonstrate the feasibility and reliability of Moon imaging based on SYISR, which enables potential further lunar geology investigations in the future.

Since the 1950s, specular meteor radars (SMRs) have been used to study the mesosphere and lower thermosphere (MLT) dynamics. Atmospheric parameters derived from SMRs are highly dependent on the number of detected meteors and the accuracy of the meteors' locations. Recently, incoherent and coherent multiple-input-multiple-output (MIMO) radar approaches combined with waveform diversity have been proposed to increase the number of detected meteors and to improve time, altitude, and horizontal resolution of the estimated wind fields. The incoherent MIMO approach refers to the addition of new transmit sites (widely separated), whereas the coherent MIMO refers to the addition of new transmit antennas in the same site (closely separated). In both the cases, a different pseudorandom sequence is transmitted from each antenna element. Unfortunately, the addition of new transmit antennas with different code sequences degrades the performance of conventional signal recovery algorithms. This is a consequence of the cross-interference between the transmitted waveforms, making it worse as the number of transmitters increases. In this article, we propose a signal recovery approach based on compressed sensing, taking advantage of the sparse nature of specular meteor echoes. The approach allows the exact recovery of weak echoes even in interference environments. Besides the advantage of the proposed approach to recover the meteor signal, we discuss the optimal selection of the transmitted waveforms and the minimum code length required for exact recovery. Additionally, we propose a modification of the orthogonal matching pursuit algorithm used in sparse problems to make it applicable in real-time analysis of large data. The success of the proposed approach is corroborated using Monte Carlo simulations and real data from a multi-static spread spectrum meteor radar network installed in northern Germany.

Multiple-input multiple-output (MIMO) radar techniques make use of multiple transmitters and multiple receivers to improve the spatial characterization of targets. In the case where the Bragg scattering k→-vector can be assumed to be the same for all transmit-receive paths, MIMO methods can be seen as a way of increasing the number of effective receivers. In the last decades, there has been scientific interest in determining the spatial characteristics of ionospheric and atmospheric irregularities on the subtransmit beam scale, allowing the study of processes in their intrinsic scales, otherwise inaccessible using simple beamforming techniques. Interferometric methods, including aperture synthesis imaging, were used in the past with a single transmitter and multiple receivers [single-input multiple-output (SIMO)]. In this paper, we present the first implementation of MIMO techniques to improve the spatial resolution of aperture synthesis radar imaging of daytime equatorial electrojet irregularities observed using the Jicamarca Radio Observatory (JRO). Our implementation uses two spatially separated transmitters and four spatially separated receivers. In order to separate the contributions of each transmitter, time, code, and polarization diversity experiments have been tested. We find that all three diversity approaches can be used for ionospheric irregularities, but time and polarization diversity are not applicable in all situations due to the range and Doppler width of the echoes, and due to magnetoionic radio propagation effects. The results are evaluated by comparing new MIMO imaging results against the currently used SIMO imaging technique. We present and discuss the theoretical and practical aspects of the MIMO approach, so they can be applied to study other targets not only at JRO but also at other modular coherent scatter radars.

In ionospheric tomography, the atmospheric electron density is reconstructed from different electron density related measurements, most often from ground-based measurements of satellite signals. Typically, ionospheric tomography suffers from two major complications. First, the information provided by measurements is insufficient and additional information is required to obtain a unique solution. Second, with necessary spatial and temporal resolutions, the problem becomes very high dimensional, and hence, computationally infeasible. With Bayesian framework, the required additional information can be given with prior probability distributions. The approach then provides physically quantifiable probabilistic interpretation for all model variables. Here, Gaussian Markov random fields (GMRFs) are used for constructing the prior electron density distribution. The use of GMRF introduces sparsity to the linear system, making the problem computationally feasible. The method is demonstrated over Fennoscandia with measurements from global navigation satellite system (GNSS) and low Earth orbit (LEO) satellite receiver networks, GNSS occultation receivers, LEO satellite Langmuir probes, and ionosonde and incoherent scatter radar measurements.

The Kilpisjärvi Atmospheric Imaging Receiver Array (KAIRA) is a dual array of omnidirectional VHF radio antennas located near Kilpisjärvi, Finland. It is operated by the Sodankylä Geophysical Observatory. It makes extensive use of the proven LOFAR antenna and digital signal-processing hardware, and can act as a stand-alone passive receiver, as a receiver for the European Incoherent Scatter (EISCAT) very high frequency (VHF) incoherent scatter radar in Tromsø, or for use in conjunction with other Fenno-Scandinavian VHF experiments. In addition to being a powerful observing instrument in its own right, KAIRA will act as a pathfinder for technologies to be used in the planned EISCAT_3-D phased-array incoherent scatter radar system and participate in very long baseline interferometry experiments. This paper gives an overview of KAIRA, its principal hardware and software components, and its main science objectives. We demonstrate the applicability of the radio astronomy technology to our geoscience application. Furthermore, we present a selection of results from the commissioning phase of this new radio observatory.

Matched filtering of quadriphase coded radar signals creates unwanted sidelobes, which may mask important information. This correspondence presents a method of eliminating these sidelobes in aperiodic quadriphase codes. This is done by using a mismatched filter. The signal-to-noise ratio (SNR) at the output of the mismatched filter is less than the SNR at the output of the corresponding matched filter. A thorough computer search has been carried out to find quadriphase code-mismatched filter pairs with minimum possible SNR losses by considering a point target in the presence of white Gaussian noise. The phase patterns of the optimal codes, which were chosen from a total number of 1.466 times 1012investigated codes, are shown. It turned out that the mismatched filter of a quadriphase Barker code with 15 elements (1, 1, 1,j,j, 1, -j, -j,j, -1, -j,j, 1, -1, 1) has a loss in SNR of only 6.7% when compared with the corresponding matched filter. The mismatched filter of the well known 13-element Barker code, which has a loss in SNR of 4.8%, outperforms this filter. Finally, using numerical experiment it is shown that a randomly selected long code will most likely have very large SNR losses.

This article presents a graphics software architecture for next-generation digital television receivers. We propose that such receivers should include a standardised Java-based procedural environment capable of rendering 2D/3D graphics and video, and a declarative environment supporting W3C recommendations such as SMIL and XForms. We also introduce a graphics architecture model that meets such requirements. As a proof-of-concept, a prototype implementation of the model is presented. This implementation enhances television content by allowing the user to play 3D graphics games, to run Java applications, and to browse XML-based documents while meeting current hardware restrictions.