Ultrasound localization microscopy to image and assess microvasculature in a rat kidney.

The recent development of ultrasound localization microscopy, where individual microbubbles (contrast agents) are detected and tracked within the vasculature, provides new opportunities for imaging the vasculature of entire organs with a spatial resolution below the diffraction limit. In stationary tissue, recent studies have demonstrated a theoretical resolution on the order of microns. In this work, single microbubbles were localized in vivo in a rat kidney using a dedicated high frame rate imaging sequence. Organ motion was tracked by assuming rigid motion (translation and rotation) and appropriate correction was applied. In contrast to previous work, coherence-based non-linear phase inversion processing was used to reject tissue echoes while maintaining echoes from very slowly moving microbubbles. Blood velocity in the small vessels was estimated by tracking microbubbles, demonstrating the potential of this technique to improve vascular characterization. Previous optical studies of microbubbles in vessels of approximately 20 microns have shown that expansion is constrained, suggesting that microbubble echoes would be difficult to detect in such regions. We therefore utilized the echoes from individual MBs as microscopic sensors of slow flow associated with such vessels and demonstrate that highly correlated, wideband echoes are detected from individual microbubbles in vessels with flow rates below 2 mm/s

Cramer-Rao bounds in the estimation of time of arrival in fading channels

This paper computes the Cramer-Rao bounds for the time of arrival estimation in a multipath Rice and Rayleigh fading scenario, conditioned to the previous estimation of a set of propagation channels, since these channel estimates (correlation between received signal and the pilot sequence) are sufficient statistics in the estimation of delays. Furthermore, channel estimation is a constitutive block in receivers, so we can take advantage of this information to improve timing estimation by using time and space diversity. The received signal is modeled as coming from a scattering environment that disperses the signal both in space and time. Spatial scattering is modeled with a Gaussian distribution and temporal dispersion as an exponential random variable. The impact of the sampling rate, the roll-off factor, the spatial and temporal correlation among channel estimates, the number of channel estimates, and the use of multiple sensors in the antenna at the receiver is studied and related to the mobile subscriber positioning issue. To our knowledge, this model is the only one of its kind as a result of the relationship between the space-time diversity and the accuracy of the timing estimation.Peer ReviewedPostprint (published version

An extensive and autonomous deep space navigation system using radio pulsars

Interstellar navigation poses significant challenges in all aspects of a spacecraft. One of them is reliable, low-cost, real-time navigation, especially when there is a considerable distance between Earth and the spacecraft in question. In this paper, a complete system for navigation using pulsar radio emissions is described and analysed. The system uses a pulsar‟s emissions in the radio spectrum to create a novel system capable of fully autonomous navigation. The system is roughly divided into two parts, the front - end and the back - end, as well as their subdivisions. The front - end performs initial signal reception and pre-processing. It applies time-based coherent de-dispersion to allow for low-power on-board processing, and uses a very wide bandwidth to limit the required antenna size. As a result, the electronics required performing the processing is complex, but the system is well limited in both size and power consumption

Efficient Transmit Beamspace Design for Search-free Based DOA Estimation in MIMO Radar

In this paper, we address the problem of transmit beamspace design for multiple-input multiple-output (MIMO) radar with colocated antennas in application to direction-of-arrival (DOA) estimation. A new method for designing the transmit beamspace matrix that enables the use of search-free DOA estimation techniques at the receiver is introduced. The essence of the proposed method is to design the transmit beamspace matrix based on minimizing the difference between a desired transmit beampattern and the actual one under the constraint of uniform power distribution across the transmit array elements. The desired transmit beampattern can be of arbitrary shape and is allowed to consist of one or more spatial sectors. The number of transmit waveforms is even but otherwise arbitrary. To allow for simple search-free DOA estimation algorithms at the receive array, the rotational invariance property is established at the transmit array by imposing a specific structure on the beamspace matrix. Semi-definite relaxation is used to transform the proposed formulation into a convex problem that can be solved efficiently. We also propose a spatial-division based design (SDD) by dividing the spatial domain into several subsectors and assigning a subset of the transmit beams to each subsector. The transmit beams associated with each subsector are designed separately. Simulation results demonstrate the improvement in the DOA estimation performance offered by using the proposed joint and SDD transmit beamspace design methods as compared to the traditional MIMO radar technique.Comment: 32 pages, 10 figures, submitted to the IEEE Trans. Signal Processing in May 201

Filtering random layering effects in imaging

Objects that are buried deep in heterogeneous media produce faint echoes which are difficult to distinguish from the backscattered field. Sensor array imaging in such media cannot work unless we filter out the backscattered echoes and enhance the coherent arrivals that carry information about the objects that we wish to image. We study such filters for imaging in strongly backscattering, finely layered media. The filters are based on a travel time transformation of the array data, the normal move-out, used frequently in connection with differential semblance velocity estimation in seismic imaging. In a previous paper [10] we showed that the filters can be used to remove coherent signals from strong plane reflectors. In this paper we show theoretically and with extensive numerical simulations that these filters, based on the normal move-out, can also remove the incoherent arrivals in the array data that are due to fine random layering in the medium. Key words. array imaging, randomly layered media, filtering

Energy and Flux Measurements of Ultra-High Energy Cosmic Rays Observed During the First ANITA Flight

The first flight of the Antarctic Impulsive Transient Antenna (ANITA) experiment recorded 16 radio signals that were emitted by cosmic-ray induced air showers. For 14 of these events, this radiation was reflected from the ice. The dominant contribution to the radiation from the deflection of positrons and electrons in the geomagnetic field, which is beamed in the direction of motion of the air shower. This radiation is reflected from the ice and subsequently detected by the ANITA experiment at a flight altitude of 36km. In this paper, we estimate the energy of the 14 individual events and find that the mean energy of the cosmic-ray sample is 2.9 EeV. By simulating the ANITA flight, we calculate its exposure for ultra-high energy cosmic rays. We estimate for the first time the cosmic-ray flux derived only from radio observations. In addition, we find that the Monte Carlo simulation of the ANITA data set is in agreement with the total number of observed events and with the properties of those events.Comment: Added more explanation of the experimental setup and textual improvement

Differential Phase Estimation with the SeaMARC II Bathymetric Sidescan Sonar System

A maximum-likelihood estimator is used to extract differential phase measurements from noisy seafloor echoes received at pairs of transducers mounted on either side of the SeaMARC II bathymetricsidescan sonar system. Carrier frequencies for each side are about 1 kHz apart, and echoes from a transmitted pulse 2 ms long are analyzed. For each side, phase difference sequences are derived from the full complex data consisting of base-banded and digitized quadrature components of the received echoes. With less bias and a lower variance, this method is shown to be more efficient than a uniform mean estimator. It also does not exhibit the angular or time ambiguities commonly found in the histogram method used in the SeaMARC II system. A figure for the estimation uncertainty of the phasedifference is presented, and results are obtained for both real and simulated data. Based on this error estimate and an empirical verification derived through coherent ping stacking, a single filter length of 100 ms is chosen for data processing application

MIMO radar space–time adaptive processing using prolate spheroidal wave functions

In the traditional transmitting beamforming radar system, the transmitting antennas send coherent waveforms which form a highly focused beam. In the multiple-input multiple-output (MIMO) radar system, the transmitter sends noncoherent (possibly orthogonal) broad (possibly omnidirectional) waveforms. These waveforms can be extracted at the receiver by a matched filterbank. The extracted signals can be used to obtain more diversity or to improve the spatial resolution for clutter. This paper focuses on space–time adaptive processing (STAP) for MIMO radar systems which improves the spatial resolution for clutter. With a slight modification, STAP methods developed originally for the single-input multiple-output (SIMO) radar (conventional radar) can also be used in MIMO radar. However, in the MIMO radar, the rank of the jammer-and-clutter subspace becomes very large, especially the jammer subspace. It affects both the complexity and the convergence of the STAP algorithm. In this paper, the clutter space and its rank in the MIMO radar are explored. By using the geometry of the problem rather than data, the clutter subspace can be represented using prolate spheroidal wave functions (PSWF). A new STAP algorithm is also proposed. It computes the clutter space using the PSWF and utilizes the block-diagonal property of the jammer covariance matrix. Because of fully utilizing the geometry and the structure of the covariance matrix, the method has very good SINR performance and low computational complexity