Emitter Location Research Articles

Signal Emitters Localization by Spectral Methods

Methods are considered of generating signals in a radar sensor receiver provided with a colocated antenna system of Multiple Input Multiple Output (MIMO) configuration when synthesizing virtual antenna arrays. Review of the basic spectral methods used in beamforming with digital automobile radars, such as Capon method, MUSIC and ESPRIT was carried out. Spatial spectra obtained by various methods were constructed for a radar signal model, and comparative spectra characteristic by angular resolution is provided. Output heatmaps in the angle-distance coordinate were constructed to represent methods operation according to the real target situation based on data sampling from the front-mounted automobile radar. Advantages of decomposition methods based on MUSIC and ESPRIT algorithms in solving the problem of a signal emitter localization are presented

Localization Microscopy

AbstractSingle‐molecule localization microscopy (SMLM) denotes a family of super‐resolution optical fluorescence imaging techniques that overcome the Abbe diffraction barrier, which normally restricts the lateral optical resolution to 200 to 300 nm. The fundamental principle of all SMLM implementations is the localization of individual fluorescence emitters by detecting their photon emission at a certain position and time in the complete absence of emission from neighboring emitters. The centroid of the diffraction‐limited distribution of photons is a measure of the location of the emitter and much better defined than the photon distribution itself. Thus, whereas a standard widefield image is an overlay of the photon distributions from a large number of emitters, a super‐resolved SMLM image is a map of their individual locations.

H.E.S.S. and Fermi-LAT observations of PSR B1259–63/LS 2883 during its 2014 and 2017 periastron passages

Context. PSR B1259–63/LS 2883 is a gamma-ray binary system consisting of a pulsar in an eccentric orbit around a bright Oe stellar-type companion star that features a dense circumstellar disc. The bright broad-band emission observed at phases close to periastron offers a unique opportunity to study particle acceleration and radiation processes in binary systems. Observations at gamma-ray energies constrain these processes through variability and spectral characterisation studies. Aims. The high- and very-high-energy (HE, VHE) gamma-ray emission from PSR B1259–63/LS 2883 around the times of its periastron passage are characterised, in particular, at the time of the HE gamma-ray flares reported to have occurred in 2011, 2014, and 2017. Short-term and average emission characteristics of PSR B1259–63/LS 2883 are determined. Super-orbital variability is searched for in order to investigate possible cycle-to-cycle VHE flux changes due to different properties of the companion star’s circumstellar disc and/or the conditions under which the HE gamma-ray flares develop. Methods. Spectra and light curves were derived from observations conducted with the H.E.S.S-II array in 2014 and 2017. Phase-folded light curves are compared with the results obtained in 2004, 2007, and 2011. Fermi-LAT observations from 2010/11, 2014, and 2017 are analysed. Results. A local double-peak profile with asymmetric peaks in the VHE light curve is measured, with a flux minimum at the time of periastron tp and two peaks coinciding with the times at which the neutron star crosses the companion’s circumstellar disc (~tp ± 16 d). A high VHE gamma-ray flux is also observed at the times of the HE gamma-ray flares (~tp + 30 d) and at phases before the first disc crossing (~tp − 35 d). The spectral energy range now extends to below 200 GeV and up to ~45 TeV. Conclusions. PSR B1259–63/LS 2883 displays periodic flux variability at VHE gamma-rays without clear signatures of super-orbital modulation in the time span covered by the monitoring of the source with the H.E.S.S. telescopes. This flux variability is most probably caused by the changing environmental conditions, particularly at times close to periastron passage at which the neutron star is thought to cross the circumstellar disc of the companion star twice. In contrast, the photon index remains unchanged within uncertainties for about 200 d around periastron. At HE gamma-rays, PSR B1259–63/LS 2883 has now been detected also before and after periastron, close to the disc crossing times. Repetitive flares with distinct variability patterns are detected in this energy range. Such outbursts are not observed at VHEs, although a relatively high emission level is measured. The spectra obtained in both energy regimes displays a similar slope, although a common physical origin either in terms of a related particle population, emission mechanism, or emitter location is ruled out.

Use of Doppler and Doppler Rate for RF Geolocation Using a Single LEO Satellite

A passive radio frequency (RF) geolocation solution is provided that uses a single low earth orbit (LEO) satellite to find an uncooperative earth-bound emitter. For the first time, an unambiguous solution is available for real-time, single-pass, and time-constrained acquisition scenarios where single transmissions are expected. The geolocation algorithm rapidly maps Doppler and Doppler rate measurements to an RF emitter location. Corresponding theoretic performance bounds are provided for mission analysis and optimality comparison. The proposed algorithm is a variant of the constrained Unscented Kalman Filter (cUKF), chosen for computational efficiency, modeling abilities, and ease of constraint incorporation. A novel, low-computation method of sigma point projection upon the surface of the earth is derived that drastically improves search area capabilities and convergence rates. The theoretical performance bound is in the form of the recursive constrained Posterior Cramer-Rao Bound (rcPCRB), which is uniquely suited to gauge the mean squared error optimality of iterative nonlinear estimation algorithms. Numerical analysis over measurement noise, center frequency, slant angle, and initialization error exhibit the algorithm’s robustness over various mission types. The performance of the cUKF is demonstrated on raw IQ data acquired from the TDS-1 satellite operated by Surrey Satellites.

Gauss Hermite H ∞ Filter for UAV Tracking Using LEO Satellites TDOA/FDOA Measurement—Part I

The precision geolocation and target tracking problem has been addressed in this paper using High-Degree Non-linear Filtering based on hybrid Time Difference of Arrival (TDOA), Frequency Difference of Arrival (FDOA) measurements using Low Earth Orbit (LEO) satellite with slant range. In order to update the noise covariance and estimation process at each measurement, the Gauss Hermite H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> Filter based on hybrid TDOA/FDOA geolocation measurements are proposed in this work. Numerous scenarios with the different rotation speed of Radio Frequency (RF) emitter has been considered. Multi LEO satellites have used to estimate and track the location of the unknown Unmanned Aerial Vehicle (UAV) under uncertainties of measurements. The uncertainties of measurements have been considered because the position and velocity of sensors are not fixed, which may affect the emitter location estimation measurements. The Cramer-Rao Lower Bound (CRLB) is used as a metric for measuring and analyzing the performance of the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> /GHKF 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> degree and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> /GHKF 5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> degree algorithm, as well as compare it with state-of-the-art algorithms. The simulation results of the proposed algorithm indicate that the significant improvement in performance for example, 10% based on TDOA, 40% for FDOA, and 50% on TDOA/FDOA have been achieved.

Joint Scan Rate and Emitter Location Estimation Algorithm in SBR System Based on AOA and DTOST Measurements

A joint scan rate and emitter location estimation algorithm in scan-based radar (SBR) system based on the angle-of-arrival (AOA) and the difference time of scan time (DTOST) measurements is proposed in this paper. SBR localization is a kind of passive geolocation technique for stationary pulsed radars. To date, a huge number of passive localization techniques using AOA, DTOST or other measurements for SBR have been developed assuming prior knowledge of the scan rate. However, it is usually hard to obtain the accurate scan velocity in most of practical civilian and military applications. In this paper, by using the linear correlation between AOA and DTOST, the maximum likelihood (ML) estimation algorithm based on linear constraints is given to obtain the scan rate of SBR. And the new AOA information after fusion is acquired on this basis. Then the weighted least square (WLS) method is used for SBR localization and the Cramer-Rao lower bound (CRLB) is derived for SBR location estimation. A detailed analysis of scan rate and emitter location estimation process is given and the effectiveness of the proposed localization algorithm is illustrated with computer simulations.

A Method Exploiting Compressive Sampling for Localization of Radio Frequency Emitters

This article presents a novel method for radio frequency (RF) emitter localization by using wideband spectrum sensors (WSSs) exploiting compressive sampling (CS). The method assumes that $R$ receivers with known Cartesian coordinates in the plane are deployed in the area, where the transmitters are expected to be. By using a nonuniform sampling (NUS) scheme, each WSS allows one to relax the throughput requirements for the data acquisition and transmission tasks. The mathematical description followed by numerical analysis is presented. Then, hardware implementation for the receiver was realized, by using commercial off-the-shelf components. The obtained results from simulation tests are reported, and an experimental assessment of the proposed method is provided. The experimental results are compared with those obtained by applying the maximum likelihood (ML) algorithm on the samples acquired according to the Nyquist criteria. As a figure-of-merit, the compression ratio (CR) of the proposed NUS scheme was evaluated and it was experimentally obtained that even for CR = 64 the spectrum reconstruction is acceptable for being used in the ML algorithm.

Designing Conservative Sensor Detection Systems With the Scan Statistic Under Emitter Location Uncertainty

When designing a sensor system to detect a target emitter in a region of interest, a fusion rule based on the scan statistic can provide improved detection performance when the emitter is uniformly distributed in the region; however, in many applications, the distribution of the emitter location is unknown. In these cases, a possible approach is to design the system considering a least favorable distribution for the emitter location. It is however difficult to find such a distribution because of the difficulty in computing the probabilities of false alarm $({P_{FA}})$ and detection $({P_D})$ of the scan statistic. To circumvent this difficulty, this paper proposes both lower and upper bounds for ${P_D}$ , and presents a procedure to obtain a tight lower bound. With these bounds and procedure, systems that ensure a minimum ${P_D}$ under a ${P_{FA}}$ constraint can be designed.

Improving the Energy Efficiency of Diffraction Optical Elements for 3D Nanoscopy

A way of improving the energy efficiency of diffraction optical elements (DOEs) that form two-lobe light fields whose intensity distribution rotates in propagation is studied. Such DOEs find application in ultrahigh resolution microscopy to modify the spread function of a point light source via phase spatial light beam modulation, allowing all three spatial coordinates of point emitting objects to be reconstructed with nanometric accuracy. Enhancing the energy efficiency of diffraction optical elements is essential for improving the accuracy of point emitter localization in the longitudinal direction (along the Z-axis).

Coherent Estimation of Three Positioning Measurements for Unknown Frequency-Hopping Signals in Passive Emitter Localization

Due to the superior anti-interception performance and inherent security features, the wide applications of frequency-hopping (FH) signals bring a great challenge to the reconnaissance and monitoring of FH emitters. This paper addresses the problem of positioning measurement estimation for unknown FH signals in passive localization, considering the range migration (RM) and Doppler frequency migration (DFM) of the maneuvering target within the observation time. A coherent range difference (RD), range rate difference (RRD) and acceleration difference (AD) estimation algorithm based on scaled Fourier transform and scaled non-uniform fast Fourier transform is proposed. This method can effectively remove RM and random DFM effects regardless of varied carrier frequency and achieve the coherent estimation of RD, RRD and AD. The whole estimation process can be easily implemented by complex multiplications combined with fast Fourier transform (FFT) and inverse FFT operations without any brute-force searching procedure. Numerical experiments demonstrate that the anti-noise performance of the proposed method is superior to several representative methods and comparable to the optimal maximum likelihood estimator with a much lower computational cost.

Computationally efficient TDOA, FDOA and differential Doppler rate estimation algorithm for passive emitter localization

This paper addresses the joint time difference of arrival (TDOA), frequency difference of arrival (FDOA) and differential Doppler rate estimation problem in passive emitter localization, considering the range and Doppler frequency migrations during the observation time. A computationally efficient estimation algorithm via second-order keystone transform and Lv's distribution is proposed. This method can effectively remove two types of migrations and accomplish the parameter estimation. Cross-terms suppression ability of the proposed method is also analyzed and its characteristic indicates the applicability in the scenario of multi-targets. The whole estimation step can be fast implemented by complex multiplications, fast Fourier transform (FFT) and inverse FFT operations without any searching procedure. Extensive numerical experiments validate that with a much lower computational cost, the proposed method could achieve comparable estimation performance with the maximum likelihood estimator and outperforms the other representative algorithms.

Sub-20 nm Core-Shell-Shell Nanoparticles for Bright Upconversion and Enhanced Förster Resonant Energy Transfer.

Upconverting nanoparticles provide valuable benefits as optical probes for bioimaging and Förster resonant energy transfer (FRET) due to their high signal-to-noise ratio, photostability, and biocompatibility; yet, making nanoparticles small yields a significant decay in brightness due to increased surface quenching. Approaches to improve the brightness of UCNPs exist but often require increased nanoparticle size. Here we present a unique core-shell-shell nanoparticle architecture for small (sub-20 nm), bright upconversion with several key features: (1) maximal sensitizer concentration in the core for high near-infrared absorption, (2) efficient energy transfer between core and interior shell for strong emission, and (3) emitter localization near the nanoparticle surface for efficient FRET. This architecture consists of β-NaYbF4 (core) @NaY0.8-xErxGd0.2F4 (interior shell) @NaY0.8Gd0.2F4 (exterior shell), where sensitizer and emitter ions are partitioned into core and interior shell, respectively. Emitter concentration is varied (x = 1, 2, 5, 10, 20, 50, and 80%) to investigate influence on single particle brightness, upconversion quantum yield, decay lifetimes, and FRET coupling. We compare these seven samples with the field-standard core-shell architecture of β-NaY0.58Gd0.2Yb0.2Er0.02F4 (core) @NaY0.8Gd0.2F4 (shell), with sensitizer and emitter ions codoped in the core. At a single particle level, the core-shell-shell design was up to 2-fold brighter than the standard core-shell design. Further, by coupling a fluorescent dye to the surface of the two different architectures, we demonstrated up to 8-fold improved emission enhancement with the core-shell-shell compared to the core-shell design. We show how, given proper consideration for emitter concentration, we can design a unique nanoparticle architecture to yield comparable or improved brightness and FRET coupling within a small volume.

DPD with IPF and GD method

The localisation of a stationary emitter with several separated sensors is studied. At low signal-to-noise ratio, the direct position determination (DPD) approach is more precise than the two-step method which estimates the time difference of arrival (TDOA) first and locates the emitter by the TDOAs. However, the exhaustive search is usually employed to find the global maximum since the object function of DPD is non-convex. After analysing the characteristics of the object function, a DPD with improved particle filter and gradient descent method (GDIPF-DPD) is proposed. The initial and fine estimations are provided by the IPF and GD methods, successively, as the object function has single peak around the expected position and is differentiable. The IPF decreases the times of resampling through mapping the particle weights before normalisation into 0–1. The GD method improves the accuracy by seeking within the single peak. Furthermore, the position Cramér–Rao lower bound of DPD with attenuation coefficient is derived and proved to be consistent with the two-step method of TDOA. Simulation results indicate that the position accuracy of the proposed algorithm is equivalent with grad search method and its computation cost is less by two orders of magnitude.

Computationally efficient TDOA and FDOA estimation algorithm in passive emitter localisation

This study addresses the joint time difference of arrival (TDOA) and frequency difference of arrival (FDOA) estimation problem in passive emitter localisation, involving range migration during the observation time. A computational efficient estimation algorithm based on scaled Fourier transformation is proposed. This method can effectively remove the RM and accomplish the parameter estimation. Cross-terms suppression ability of the proposed method is also analysed and its characteristic indicates the applicability in the scenario of multi-targets. The whole estimation step can be fast implemented by complex multiplications, fast Fourier transformation (FFT) and inverse FFT without any searching process. Compared with the ideal maximum likelihood estimator via extensive numerical experiments, the proposed method can achieve comparable estimation performance and have gained more than ten thousand times reduction in the computational cost, which helps practical application.

Bayesian Multiple Emitter Fitting using Reversible Jump Markov Chain Monte Carlo

In single molecule localization-based super-resolution imaging, high labeling density or the desire for greater data collection speed can lead to clusters of overlapping emitter images in the raw super-resolution image data. We describe a Bayesian inference approach to multiple-emitter fitting that uses Reversible Jump Markov Chain Monte Carlo to identify and localize the emitters in dense regions of data. This formalism can take advantage of any prior information, such as emitter intensity and density. The output is both a posterior probability distribution of emitter locations that includes uncertainty in the number of emitters and the background structure, and a set of coordinates and uncertainties from the most probable model.

Graphene-based metal-induced energy transfer for sub-nanometre optical localization

Single-molecule fluorescence imaging has become an indispensable tool for almost all fields of research, from fundamental physics to the life sciences. Among its most important applications is single-molecule localization super-resolution microscopy (SMLM) (for example, photoactivated localization microscopy (PALM)1, stochastic optical reconstruction microscopy (STORM)2, fluorescent PALM (fPALM)3, direct STORM (dSTORM)4 and point accumulation for imaging in nanoscale topography (PAINT)5), which uses the fact that the centre position of a single molecule’s image can be determined with much higher accuracy than the size of that image itself. However, a big challenge of SMLM is to achieve super-resolution along the third dimension as well. Recently, metal-induced energy transfer (MIET) was introduced to axially localize fluorescent emitters6–9. This exploits the energy transfer from an excited fluorophore to plasmons in a thin metal film. Here, we show that by using graphene as the ‘metal’ layer, one can increase the localization accuracy of MIET by nearly tenfold. We demonstrate this by axially localizing single emitters and by measuring the thickness of lipid bilayers with angstrom accuracy. Using graphene as the ‘metal’ layer can increase the localization accuracy of metal-induced energy transfer, enabling axial localization of single emitters and measurement of the thickness of lipid bilayers with angstrom accuracy.

Noniterative Three-Dimensional Location Estimation Using Azimuth and Elevation Measurements at Multiple Locations

Closed-form expression of three-dimensional emitter location estimation using azimuth and elevation measurements at multiple locations is presented in this paper. The three-dimensional location estimate is obtained from three-dimensional sensor locations and the azimuth and elevation measurements at each sensor location. Since the formulation is not iterative, it is not computationally intensive and does not need initial location estimate. Numerical results are presented to show the validity of the proposed scheme.

Direct Position Determination Sensitivity to NLOS Propagation Effects on Doppler-Shift

In this paper, we consider the Direct Position Determination (DPD) algorithm for Doppler-shift based localization of radio-emitters. The DPD emitter location estimate is the location candidate that maximizes the largest eigenvalue of a location-dependent matrix. The sensitivity to multipath is analyzed by Small Error Analysis, which requires expressions for the derivatives of the largest eigenvalue with respect to the multipath parameters. We consider multipath conditions in which the line-of-sight path is obstructed and the receivers intercept a non-line-of-sight (NLOS) component. We provide compact closed-form expressions for these derivatives. Our theoretical results are corroborated by numerical experiments.

Effect of different sand filter underdrain designs on emitter clogging using reclaimed effluents

Sand media filters are those that achieve a higher retention of organic and inorganic solids, which is why they are usually recommended when reclaimed effluents are used in drip irrigation systems. Sand filters usually differ on the design of their underdrain, where an important pressure drop is produced. However, the effect of the design of sand filter underdrain on emitter clogging has not been widely studied. Three sand media filters with different underdrain designs (collector arms, inserted domes and drainage with porous media) were used for filtering a reclaimed effluent in a surface drip irrigation system. Pressure-compensating emitters with 2.3 l/h nominal emitter discharge were placed every 40 cm in 4 irrigation laterals each measuring 90 m in length. Effluents were chlorinated after being filtered. The filters operated for 1000 h with sand media heights of 20 and 30 cm and filtration velocities of 30 and 60 m/h. At the beginning, after 500 h, and at the end of the experiment the emitter discharge of each one of the 2712 emitters that were installed was experimentally measured under field conditions. On average, there was a statistically significant reduction (p < 0.05) on emitter discharge regarding the initial value of 8.03% at 500 h and 10.84% at 1000 h. Emitter clogging was primarily affected by the interactions between underdrain design, emitter location and irrigation time. Differences on emitter discharge due to underdrain design were only observed at 1000 h, showing a significantly higher flow rate (p < 0.05) those emitters protected with the filter with a collector arm underdrain, despite the fact that this filter did not achieve the highest turbidity removals. Emitter location had also a significant effect after 500 h of operation, being discharge significantly lower (p < 0.05) only in the last 2 m of the laterals, with the minimum values found for the final two drippers. The three filters used in the experiment did not show a significant effect on the percentage of completely clogged emitters, which mainly depended on the interaction between irrigation time and emitter location.

Direct Localization of Emitters Based on Sparse Bayesian Learning

In this paper, a novel perspective for the problem of direct localization of emitters is presented based on sparse Bayesian learning (SBL). The localization problem is addressed in three scenarios, where we derive the angle-of-arrival (AOA) based models for two kinds of narrowband conditions and the model jointly taking use of time-difference-of-arrival (TDOA) and AOA information. Unlike the existing $\ell _1$ -penalization based direct localization methods, we expand the localization models to the sparsity-based framework with the scheme of SBL, which makes the partly unknown dictionary based problems solvable. On the basis of the bound-optimization SBL algorithm, modifications are provided to make its solving procedures adapt to the localization models. For one thing, the learning rule of channel attenuation factors (i.e., the unknown part of the dictionaries) is added in the solving procedures. For another, we expand the original single measurement vector (SMV) based model to the multiple measurement vector (MMV) scenario. Furthermore, we modify the original procedures by updating the parameters with an alternating minimization strategy, which guarantees the convergence of the algorithms. Simulation results show the features of three SBL-based models and the performance superiority of the proposed methods.