Identification Of Echoes Research Articles

Towerpy: An open-source toolbox for processing polarimetric weather radar data

Weather radars produce high spatial and temporal resolution observations of precipitation events. Over the years, weather radar operators have updated their radar networks to exploit the latest technological advancements. One of the most significant improvements in this matter was providing the radars with polarimetric capabilities, as this allows the radars to gather more detailed information about the precipitation targets’ shape, size, phase, and orientation. The radar research community has been working along with these advancements to develop robust algorithms that boost the radar data applications, such as radar quantitative precipitation estimation (QPE), rain microphysics analysis, nowcasting of precipitation or numerical weather prediction based on radar measurements. Some of these algorithms have been implemented in open-source toolboxes that aim to facilitate the processing and quality control of radar data produced by different radar systems. However, these open-source projects have not yet included a chain process tailored to the UK radar research context. This paper presents a TOolbox to process WEather Radar data in PYthon (Towerpy). Towerpy can read, process and display polarimetric radar data from different radar systems, but it is specially customised for data produced by the UK Met Office radar network. Towerpy is built upon robust algorithms that cover various aspects of the radar data quality control (e.g., calibration of radar measurements, identification of non-meteorological echoes, attenuation correction, among others) and the computation of radar rainfall rates. Additionally, a radar processing chain was devised using the Towerpy modules to produce radar rainfall estimates. Raw polarimetric radar measurements collected by the UK Met Office radar network throughout the UK’s wettest day on record were used as input for this processing chain. The results confirm that Towerpy is a powerful radar research tool and demonstrate its ability to generate functional radar QPE that can be used to improve operational radar rainfall products.

Ultrasonic defect detection in noisy signals by a nonconvex sparse regularization approach

Ultrasonic testing has been an important tool for the detection of hidden defects in materials yet its effectiveness is usually compromised by the noise originated from both the testing system and the material being evaluated. Motivated by the prior knowledge that only a small number of defects or reflectors exist within the tested material thus the measured signal can be viewed as a linear combination of a few echoes, a signal processing method is proposed in this study where a nonconvex sparse regularization method based on lp-norm (0 < p < 1) penalty is employed to suppress noises in ultrasonic NDT signals thus enhancing the effectiveness and accuracy of flaw detection. Based on a specially designed over-complete Gabor dictionary, the nonconvex sparse regularization method is introduced to sparsely represent the noisy signal. After signal representation, noise is suppressed by a pruning operator, facilitating the identification and reconstruction of flaw-reflected echoes. The performance of the proposed method is quantitatively evaluated and compared with competing algorithms using simulated noisy ultrasonic signals in a statistical manner. Experimental results are also presented to demonstrate the effectiveness of our method.

Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Millimeter-wave cloud radar (MMCR) provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds. Therefore, MMCR has been widely applied in cloud observations. However, due to the influence of non-meteorological factors such as insects, the cloud observations are often contaminated by non-meteorological echoes in the clear air, known as clear-air echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The characteristics of clear-air echoes are studied here by combining data from four devices: an MMCR, a laser-ceilometer, an L-band radiosonde, and an all-sky camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions. The recognition accuracy can reach up to 95.86% for the simple cases when cloud echoes and clear-air echoes are separate, and 88.38% for the complicated cases when low cloud echoes and clear-air echoes are mixed.

Recent Progress in Dual-Polarization Radar Research and Applications in China

Dual-polarization (dual-pol) radar can measure additional parameters that provide more microphysical information of precipitation systems than those provided by conventional Doppler radar. The dual-pol parameters have been successfully utilized to investigate precipitation microphysics and improve radar quantitative precipitation estimation (QPE). The recent progress in dual-pol radar research and applications in China is summarized in four aspects. Firstly, the characteristics of several representative dual-pol radars are reviewed. Various approaches have been developed for radar data quality control, including calibration, attenuation correction, calculation of specific differential phase shift, and identification and removal of non-meteorological echoes. Using dual-pol radar measurements, the microphysical characteristics derived from raindrop size distribution retrieval, hydrometeor classification, and QPE is better understood in China. The limited number of studies in China that have sought to use dual-pol radar data to validate the microphysical parameterization and initialization of numerical models and assimilate dual-pol data into numerical models are summarized. The challenges of applying dual-pol data in numerical models and emerging technologies that may make significant impacts on the field of radar meteorology are discussed.

Ground moving target recognition using log energy entropy of wavelet packets

Automatic target recognition of ground surveillance radars is a beneficial practice that reduces cost, error, duration of detection and response time. The identification of echoes from eight classes using an RF pulsed Doppler radar is studied. Instead of traditional methods, the wavelet packet analysis (WPA) is used. WPA, by providing arbitrary time–frequency resolution, enables analysing signals of stationary and non-stationary nature. It has better time representation than Fourier analysis and better high-frequency resolution than wavelet analysis. WPA subimages are further analysed to obtain feature vectors of log energy entropy in all cases except one case where norm entropy is used. These features are fed into a multilayer perceptron for classification which is done in a hierarchical scheme and composed of binary classification steps. Hundred per cent accuracy was possible in all steps except two which were realised at 99.5 and 98.2%. An overall classification rate of 98.2% was achieved. The results were compared with other published results that report accuracy in the same application field. The proposed method achieved the highest accuracy although it had the highest number of classes. The method provides a promising tool for the automatic recognition of ground surveillance radar targets.

Echolocation behavior in big brown bats is not impaired after intense broadband noise exposures.

Echolocating bats emit trains of intense ultrasonic biosonar pulses and listen to weaker echoes returning from objects in their environment. Identification and categorization of echoes are crucial for orientation and prey capture. Bats are social animals and often fly in groups in which they are exposed to their own emissions and to those from other bats, as well as to echoes from multiple surrounding objects. Sound pressure levels in these noisy conditions can exceed 110 dB, with no obvious deleterious effects on echolocation performance. Psychophysical experiments show that big brown bats (Eptesicus fuscus) do not experience temporary threshold shifts after exposure to intense broadband ultrasonic noise, but it is not known if they make fine-scale adjustments in their pulse emissions to compensate for any effects of the noise. We investigated whether big brown bats adapt the number, temporal patterning or relative amplitude of their emitted pulses while flying through an acoustically cluttered corridor after exposure to intense broadband noise (frequency range 10-100 kHz; sound exposure level 152 dB). Under these conditions, four bats made no significant changes in navigation errors or in pulse number, timing and amplitude 20 min, 24 h or 48 h after noise exposure. These data suggest that big brown bats remain able to perform difficult echolocation tasks after exposure to ecologically realistic levels of broadband noise.

Identification and removal of non-meteorological echoes in dual-polarization radar data based on a fuzzy logic algorithm

A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter, chaff, clear air echoes etc. In this study, a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek. For selected precipitation and non-meteorological events, the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values. The membership functions and weights are then determined by these density functions. Finally, the nonmeteorological echoes are identified by combining the membership functions and weights. The performance is qualitatively evaluated by long-term rain accumulation. The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection (POD), false alarm rate (FAR), and clutter-signal ratio (CSR). In addition, the issues in using filtered dual-polarization data are alleviated.

Identification and Suppression of Nonmeteorological Echoes Using Spectral Polarimetric Processing

The presence of nonmeteorological radar signals, such as sea clutter, birds, and chaff, is a continuous challenge for meteorological services in different regions. In this paper, we assign membership functions to these signals using spectral decompositions of copolar correlation coefficient, differential reflectivity, and differential phase. Additionally, we apply the dual-polarization spectral decomposition technique to identify and suppress nonmeteorological echoes present in radar observations. The performance of the polarimetric spectral filter is illustrated in observations from the C-band Helsinki University Kumpula radar. The results show that the spectral polarimetric filter may be a suitable solution for the mitigation of these nonmeteorological signals.

Joint mode identification and localisation improvement of over‐the‐horizon radar with forward‐based receivers

Target tracking of over-the-horizon radar (OTHR) suffers from the effect of multi-path propagation. To date, all corresponding tracking methods depend on the precondition that the ionospheric heights should be available via the ionosondes. However, the ionosondes cannot be arbitrary deployed, for example, in sea area or hostile zone. This study presents the problem of sensor fusion of OTHR and a set of forward-based receivers (FBRs) for online mode identification of OTHR echoes, estimation of virtual ionospheric heights and localisation improvement. This fusion problem faces two challenges. The first is ‘multi-path’, as a kind of uncertainty existing in both the forward propagation of FBRs and the forward/backward propagation of OTHR. The other is ‘coupling’, representing the complexity that the mode/parameter identification and estimation couple each other. Here the joint optimisation scheme of identification and estimation is proposed mainly including four sub-processes: coordinate mapping with target height, joint identification and estimation of FBRs, mode identification of OTHR and localisation improvement. The simulation shows that propagation/clutter modes can be identified effectively and ionospheric heights are estimated without the help of ionosondes. Meanwhile, target state including the target height is estimated and the localisation accuracy is further improved due to sensor fusion.

Detection and Mitigation of Second-Trip Echo in Polarimetric Weather Radar Employing Random Phase Coding

This study presents a new identification and mitigation scheme of second trip contamination for pulsed Doppler polarimetric weather radars with the ability of random phase coding. This scheme can be easily implemented in a magnetron radar without any hardware changes. For relatively weak contamination, identification and mitigation are based on a multilag processing method, which uses multiple lags of both the auto- and cross-correlation functions to estimate radar moments. For relatively strong contamination, instantaneous phase variations of horizontal and vertical polarization channels are combined into a simple fuzzy-logic scheme to complete the identification. Data from the C-band OU-PRIME radar are used to demonstrate the effectiveness of the proposed scheme for identification and mitigation of second-trip echoes.

Synthetic and field examples of ground‐penetrating radar (GPR) profile improvement using two‐phase detection techniques

Ground-penetrating radar (GPR) has been used extensively in a wide range of subsurface imaging applications, including underground utilities, hazardous waste and liquid contaminants, buried archeologic sites, geological interfaces (fractures, bedding planes), and pavement–concrete structure assessment (Hugenschmidt, 2000; Olhoeft and Smith, 2000). In the latter case, industrial applications such as damage assessment before road rehabilitation require processing and analysis of data sets that may be orders of magnitude larger than normal GPR ones. In such conditions, the reliable identification of radar echoes in a large range of S/N ratio values can be exploited to apply automatic tracking algorithms for a cost-effective interpretation. A number of studies deal with applying GPR to pavement assessment (Hugenschmidt et al., 1998; Saarenketo and Scullion, 2000), analyzing water content in the pavement or in the subgrade (Benedetto and Benedetto, 2002; Emilsson et al., 2002), and implementing or exploiting automatic tracking algorithms to interpret GPR data sets from pavement surveys Spagnolini and Rampa, 1999). Anomalous lateral variations in water content of the pavement and subgrade are recognized as a major source of pavement damage. At the same time, they affect the radar response by causing an overall decrement of the S/N ratio, most probably because of the defects (primarily delamination and cracks) produced by the anomalous saturation. No examples exist in the available literature of dedicated processing techniques to improve the detection of weak transients in low S/N ratio conditions and to enhance the performance of automatic tracking methods. In this work we exploit wavelet transform-based instantaneous parameter analysis for this purpose and compare the results with those obtained by Hilbert transforms on synthetic and real GPR data.

Identification of Southern Ocean acoustic targets using aggregation backscatter and shape characteristics

Abstract Acoustic surveys for biomass estimation require accurate identification of echoes from the target species. In one objective technique for identifying Antarctic krill, the difference between mean volume-backscattering strength at two frequencies is used, but can misclassify small krill and other plankton. Here, we investigate ways to improve target identification by including characteristics of backscattering energy and morphology of aggregations. To do this, multi-frequency acoustic data were collected concurrently with target fishing of Antarctic krill and other euphausiid and salp aggregations. Parameter sets for these known aggregations were collated and used to develop empirical classifications. Both linear discriminant-function analysis (DFA) and the artificial neural network technique were employed. In both cases, acoustic-backscattering energy parameters were most important for discriminating between Antarctic krill and other zooplankton. However, swarm morphology and other parameters improved the discrimination, particularly between krill and salps. Our study suggests that for krill-biomass estimates, a simple DFA based on acoustic-energy parameters is a substantial improvement over current dB-difference acoustic methods; but studies requiring the discrimination of zooplankton other than krill must still be supported by target fishing.

Objective Identification of Echoes Due to Anomalous Propagation in Weather Radar Data

Abstract Serious contamination of weather radar data can occur in atmospheric conditions that cause anomalous propagation of the radar beam. Excessive downward refraction of the beam may be sufficient to cause ground returns (“anaprop”), which may be difficult to distinguish from rainfall echoes. At the U.K. Meteorological Office, an automatic scheme has been devised to combine several sources of evidence, by means of Bayesian statistics, to estimate the probability that an echo is caused by anaprop. Currently, the scheme uses hourly surface observations, Meteosat infrared images, a climatology of anaprop echoes, and detected lightning, but additional independent sources would be easy to add. Results from the automatic scheme have been compared with those from an interactive quality control procedure and show agreement of around 90% in the cases evaluated. Promising areas for extension and refinement of the scheme are suggested.

HF multipath dispersion measurements using cepstral signal processing

A technique for measuring ionospheric echo arrival times and strengths is described. The technique uses ordinary HF‐SSB transceivers and an easy to generate probe signal. It is based on the cepstral signal processing tool for deconvolution. Identification of ionospheric echoes in a received sky wave signal was viewed as a deconvolution problem, and the cepstral transformation was used to obtain information about the multipath profile of the channel. Field tests were carried out where multipath characteristics of the ionospheric channel was measured using this technique.

SPRUCE BUDWORM (LEPIDOPTERA: TORTRICIDAE) MOTH FLIGHT AND DISPERSAL: NEW UNDERSTANDING FROM CANOPY OBSERVATIONS, RADAR, AND AIRCRAFT

AbstractA research programme in New Brunswick coordinating the use of radar, specially-instrumented aircraft, and observations from platforms extending above the forest canopy has established the massive scale and regularity of evening take-off flights by spruce budworm moths, Choristoneura fumiferana, and of subsequent nocturnal dispersal at levels high above the ground. A night-viewing telescope showed moths taking off from the tree crowns up until 2330 h, 2.5 h after sunset, while radar dot echoes of uniform strength and size began to appear each night at about the same time. Direct identification of radar echoes was provided by simultaneous catches of budworm moths taken in insect-collecting nets on Cessna 185 aircraft. Moths collected during emigration, displacement, and immigration contained a high proportion of egg-carrying females.Radar recorded the rates of climb and the altitudes reached by the flying moths and provided extensive data on their numbers, density, orientation, direction, speed, and duration of displacement. Airborne moths became concentrated in zones of wind convergence, and line-echoes from moths at wind-shift fronts were detected on radar at distances of 30 km. The time of passage of wind-shift fronts over a surface site was detectable by pilot-balloon observations and by sensing equipment on a 24-m meteorological tower. Wind-fields over New Brunswick, as found from a DC-3, showed a marked contrast between the high degree of wind uniformity on many evenings and convergent winds on other evenings. Attention is focussed on the potential effects of meso-scale sea breeze fronts, of which one example is presented, and of storm cells on moth concentration and dispersal.Through the use of radar, spruce-budworm moth dispersal has been viewed for the first time in its entirety and the integrated research programme has provided new data for better evaluation of the significance of moth dispersal in the initiation and spread of infestations.

Problems in ultrasonic estimates of septal thickness

Problems related to cardiac anatomy and ultrasonic instrumentation affect the accuracy of echographic identification of endocardial echoes. A cadaver model and 13 patients were studied, with direct identification or with the aid of echographic contrast techniques, to identify accurately the endocardial echo. The study showed that (1) echographic contrast agents delineate an endocardial echo in the central portion of the ultransonic beam; (2) a specular reflector exists within the right ventricular cavity; (3) specular reflectors within the septum may give the false appearance of border-forming echoes; (4) septal thickness varies by 1 to 5 mm after the endocardial echo has been identified by the contrast agent; and (5) spurious echoes, related to a wide beam angle, can be confused with the endocardial echo. In light of these problems, three criteria were utilized for endocardial echo identification: the prominent notch in the left septal echo, the specular quality of the right septal echo, and the association of multiple myocardial echoes moving in parallel. With these criteria, the endocardial echoes in 11 of the 13 patients could be accurately identified without the use of a contrast agent. The identification of these problems should provide helpful guidelines in developing more accurate and reproducible criteria for septal thickness measurements.

An Example of The Unified Method of Interpretation for Crustal Seismic Data

Summary Two interpretations of the record section for a seismic refraction profile recorded in the Basin and Range area of western North America are presented which compare the results to be obtained from the apparent velocities and intercepts of first arrivals with those which may be found from a unified interpretation of all relevant data. The addition of nearby vertical-incidence reflection data permits the identification of separate echoes from the tops and bottoms of two separate velocity inversions which are situated above and below the intermediate layer at depths of roughly 10 and 20 + km. The four wide-angle reflection hyperbolae corresponding to these interfaces are concordant with strong and distinct wave groups in the record section, confirming the unified interpretation. Suggestions that the seismic refraction operations be curtailed, because of a supposed inability to detect intra-crustal interfaces, are questioned in the light of this result.

Identification of ultrasound echoes from the left ventricle by use of intracardiac injections of indocyanine green.

This study was designed to identify the ultrasound echoes originating from the left ventricle. Injections of indocyanine green and saline were made directly in the left ventricular cavity via a cardiac catheter in patients undergoing routine diagnostic cardiac catheterization. The injections produced a cloud of echoes that filled the left ventricular cavity and outlined the left side of the interventricular septum and the endocardial surface of the posterior left ventricular wall. The results of this study verified the origin of echoes that are vital to the ultrasound technics for the detection of pericardial effusion, left ventricular wall size, left ventricular cavity size, and left ventricular stroke volume. This study also provided ways of distinguishing between the true left ventricular wall echoes and intracavitary echoes that often cause confusion.

Classification and interpretation of Radar Weather Echoes in India

In the paper, a classification of various types of radar- weather echoes in tropics has been attempted. The different types of precipitation echoes have been categorised under the head-(l) Feature type, (2) Synoptic type and (3) Seasonal type. In order to be able to distinguish the real precipitation echoes from those due to super-refraction etc, the various types of non-precipitation echoes have been described in the second part of the paper. Classification of radar echoes has been attempted with a view to provide guidance material to meteorologists in India in the identification and interpretation of radar-weather echoes. It is based on the data so fat collected in India and is likely to be changed or modified as more experience is gained.