Passive Detection Research Articles

Virtual Array-Based Signal Detection and Carrier Frequency Offset Estimation in a Multistatic Collaborative Passive Detection System

To tackle the problem of difficult signal detection and carrier frequency synchronization faced by wireless communication among stations of the multistatic passive detection system in interference environments, an adaptive signal detection and carrier frequency offset (CFO) estimation method based on a virtual array is proposed in this paper. This is a data-aided method that utilizes a training sequence composed of three segments of sub-training sequences with different symbols. This method first uses spatial spectrum estimation to obtain the coarse frequency estimations of interference signals and CFO from virtual array signals constructed from the first two sub-training sequences. Then, beamforming is conducted accordingly on the virtual array signals constructed from the third sub-training sequence to suppress the in-band interferences and protrude the expected signal. Finally, improved performance of signal detection and CFO estimation is obtained with the beamformed signals. Simulation experiments show that a missed detection probability as low as 1 × 10−4, with a false detection probability of 1 × 10−3, can be obtained under a signal-to-interference ratio (SIR) of −10 dB and Eb/N0 of 1 dB. Moreover, the proposed method can also simultaneously achieve a CFO estimation error that is lower than 3%, with the condition of Eb/N0 being as low as −5 dB under different SIRs. Simulation results validate the proposed method and demonstrate the promising application prospects of the proposed method in networked passive detection scenarios.

Real-time mapping of photo-sono therapy induced cavitation using Doppler optical coherence tomography.

Photo-sono therapy (PST) is an innovative anti-vascular approach based on cavitation-induced spallation. Currently, passive cavitation detection (PCD) is the prevalent technique for cavitation monitoring during treatment. However, the limitations of PCD are the lack of spatial information of bubbles and the difficulty of integration with the PST system. To address this, we proposed a new, to the best of our knowledge, cavitation mapping method that integrates Doppler optical coherence tomography (OCT) with PST to visualize bubble dynamics in real time. The feasibility of the proposed system has been confirmed through experiments on vascular-mimicking phantoms and in vivo rabbit ear vessels, and the results are compared to high-speed camera observations and PCD data. The findings demonstrate that Doppler OCT effectively maps cavitation in real time and holds promise for guiding PST treatments and other cavitation-related clinical applications.

SFDM: A time-synchronization-free detection mechanism for mobile underwater acoustic sensor networks

Detection and localization are important applications of underwater acoustic sensor networks, and the use of passive listening arrays composed of multiple underwater unmanned platforms to achieve passive detection and localization of targets has been a hot research topic in recent years. However, most schemes based on mobile listening arrays only aim to improve localization accuracy, with less consideration of the high communication and time overhead of formation maintenance and the high cost of time synchronization among nodes. To reduce the cost while ensuring localization accuracy, this paper proposes a time-synchronization-free detection mechanism for mobile underwater acoustic sensor arrays. Initially, the nodes cruise underwater until they passively detect a target signal. Subsequently, a pseudo-synchronization and rough self-calibration process is triggered among the nodes, which relies on the communication among the nodes. The communication stage is based on a time-synchronization-free detection protocol. An improved sound speed stratification effect compensation algorithm and an unscented particle filter algorithm are proposed to improve the calibration accuracy of the array. Finally, the Time Difference of Arrival method is utilized to locate the target position. Simulation and sea trial results confirm the feasibility and accuracy of the proposed mechanism. In addition, the mechanism is effective in reducing hardware costs.

Research on SDP-BF Method with Low False Positive Face to Passive Detection System

With the rapid development of 5G, UAV, and military communications, the data volume obtained by the non-cooperative perception system has increased exponentially, and the distributed system has become the development trend of the non-cooperative perception system. The data distribution service (DDS) produces a significant effect on the performance of distributed non-cooperative perception systems. However, the traditional DDS discovery protocol has problems such as false positive misjudgment and high flow overhead, so it can hardly adapt to a large multi-node distributed system. Therefore, the design of a DDS discovery protocol for large distributed system is technically challenging. In this paper, we proposed SDP-DCBF-SFF, a discovery protocol based on the Dynamic Counter Bloom Filter (DCBF) and Second Feedback Filter (SFF). The proposed discovery protocol coarsely filters the interested endpoints through DCBF and then accurately screens the uninterested endpoints through SFF to eliminate the connection requests of false positive endpoints and avoid extra flow overhead. The experimental results indicate that the proposed discovery protocol could effectively reduce the network overhead, and eliminate the false positive probability of endpoints in small, medium, large, and super large systems. In addition, it adopts the self-adaptive extension mechanism of BF to reduce the reconfiguration delay of BF and achieve the smallest system transmission delay. Therefore, the proposed discovery protocol has optimal comprehensive performance and system adaptability.

The impact of the National Programme to Eliminate Lymphatic Filariasis on filariasis morbidity in Sri Lanka: Comparison of current status with retrospective data following the elimination of lymphatic filariasis as a public health problem.

Sri Lanka implemented the National Programme for Elimination of Lymphatic Filariasis (NPELF) in its endemic regions in 2002. Five annual rounds of mass drug administration using the two-drug combination diethylcarbamazine (DEC) and albendazole led to sustained reductions in infection rates below threshold levels. In 2016, WHO validated that Sri Lanka eliminated lymphatic filariasis as a public health problem. To explore the impact of the NPELF on lymphatic filariasis morbidity in Sri Lanka. Passive Case Detection (PCD) data maintained in filaria clinic registries from 2006-2022 for lymphoedema and hospital admission data for managing hydroceles/spermatoceles from 2007-2022 were analyzed. The morbidity status in 2022 and trends in overall and district-wise PCD rates were assessed. Poisson log-linear models were used to assess the trends in PCD for endemic regions, including district-wise trends and hospital admissions for the management of hydroceles/spermatoceles. In 2022, there were 566 new lymphoedema case visits. The mean (SD) age was 53.9 (16.0) years. The staging was done for 94% of cases, of which 79% were in the early stages (57.3% and 21.4% in stages two and one, respectively). Western Province had the highest caseload (52%), followed by the Southern (32%) and Northwestern (16%) Provinces, respectively. The reported lymphoedema PCD rate in 2022 was 0.61 per 10,000 endemic population. The overall PCD rate showed a decline of 7.6% (95%CI: 4.9% - 10.3%) per year (P < 0.0001) from 2007 to 2022. A steady decline was observed in Colombo, Gampaha and Kurunegala districts, while Kalutara remained static and other districts showed a decline in recent years. Further, admissions for inpatient management of hydroceles/spermatoceles showed a declining trend after 2015. The PCD rates of lymphoedema and hydroceles/spermatoceles showed a declining trend in Sri Lanka after the implementation of the NPELF.

(Invited) Battery Safety and Self-Quenching Battery Pack Concept: D3 (Dissipate, Direct, and Douse Heat and Fire)

Battery pack safety following an individual cell runaway is an important aspect to address as we pack more energy into a small volume and mass. Thermal runaway incidents are extremely rare but can be catastrophic. The runaway can be triggered by local overcharge, thermal or mechanical abuse.In this talk, we will first go into the details of thermal runaway initiation and propagation. Second, solution to quench the thermal runaway from propagating within the cell through a novel and passive detection of incipient thermal runaway temperature via thermoplastics will be introduced; and that is followed by discussion on the coolant release trigger to quench the runaway. In addition, this solution prevents propagation from cell-to-cell and reduce the chance for secondary combustion. This solution also leverages the fast thermal conductivity that is offered by the Cu and Al current collectors within the cell. The role of current collectors in relaying the information from the source of thermal runaway to the surface of the new format cell will be discussed.The solution proposed here is chemistry agnostic and can be adapted to applications such as in transportation of cells and packs, grid energy storage, and mobility. The talk concludes by describing the next steps and value chain partnerships to make this safer solution a reality.Below is an image that shows the self-quenching battery concept. Figure 1

Building High-Density Polar Hybrid Perovskites via Intercalation of Cs+ and Aromatic Diamine for Passive X-ray Detection.

2D organic-inorganic hybrid perovskites (OIHPs) have shown great promise in direct X-ray detection. The development of high-performance passive X-ray detectors in 2D OIHPs calls for an increase in material density while maintaining structural polarity, which is becoming quite challenging. Here, a high-density, polar 2D alternating-cation-intercalated (ACI) perovskite, (4-AP)Cs2Pb2I8 (B, 4-AP = 4-amidinopyridinium), capable of addressing this problem is successfully constructed by introducing heavy Cs+ into the interlayer space of an aromatic Dion-Jacobson (DJ) perovskite (4-AP)PbI4 (A). Through such a DJ-to-ACI design, the newly developed 2D OIHP B not only significantly increases its density to 4.23 g cm-3 (even higher than that of 3D MAPbI3) but also crystallizes in a polar space group (Ama2), which further leads to enhanced X-ray attenuation and an obvious polar photovoltage (1.1 V) under X-ray irradiation. As a result, X-ray detectors fabricated by high-quality single crystals of B exhibit excellent and stable detection performance under self-powered mode with a high sensitivity of 107 μC Gy-1 cm-2 and a low detection limit of 289 nGy s-1. This work provides implications for the future exploration and regulation of novel ACI OIHPs for high-performance photoelectronic devices.

Passive Vision Detection of Torch Pose in Swing Arc Narrow Gap Welding.

To enhance the synchronous detection of the horizontal and vertical positions of the torch in swing arc narrow gap welding, a torch pose detection (TPD) method is proposed. This approach utilizes passive visual sensing to capture images of the arc on the groove sidewall, using advanced image processing methods to extract and fit the arc contour. The coordinates of the arc contour center point and the highest point are determined through the arc contour fitting line. The torch center position is calculated from the average horizontal coordinates of the arc contour centers in adjacent welding images, while the height position is determined from the vertical coordinate of the arc's highest point. Experimental validation in both variable and constant groove welding conditions demonstrated the TPD method's accuracy within 0.32 mm for detecting the torch center position. This method eliminates the need to construct the wire centerline, which was a requirement in previous approaches, thereby reducing the impact of wire straightness on detection accuracy. The proposed TPD method successfully achieves simultaneous detection of the torch center and height positions, laying the foundation for intelligent detection and adaptive control in swing arc narrow gap welding.

Application research on vector coherent frequency‐domain batch adaptive line enhancement in deep water

AbstractThe low frequency line spectrum noise radiated by ships has strong stability and is difficult to eliminate, which is the key information required for passive signal detection. A vector coherent frequency‐domain batch adaptive line enhancement method is proposed to address the issue of insufficient detection capability of traditional scalar adaptive line enhancement (ALE) algorithms for ship characteristic line spectra in complex deep‐sea environments. This method not only introduces the idea of frequency‐domain batch processing, but also uses synchronously collected sound pressure and particle velocity as dual input, fully utilising the coherence characteristics between vector channels to output high gain line spectrum signals and improve computational efficiency. In simulation and sea trial data validation, compared with the time‐domain vector coherent adaptive line enhancement algorithm, this method has shorter time consumption, higher efficiency, and can improve the detection ability of line spectrum signals under low signal‐to‐noise ratio conditions. The bearing estimation results output by this algorithm is also more accurate.

Superimposed Positive Sequence Impedance for Detecting Unintentional Islanding in Microgrid

Incorporation of environmentally friendly energy sources (RESs) into the electricity grid has many benefits, including economic, technological, and environmental. However, excessive renewable energy sources (RES) in the power grid provide technical problems, including equipment protection, DG operation, and islanding detection. One of the most serious challenges is the islanding phenomenon. Islanding can cause several problems, such as frequency instability and voltage fluctuations resulting in damage to electrical equipment or threatening utility workers who may be working/accessing the equipment. This research proposes an efficient islanding detection algorithm to lessen the impact of such threats. This novel passive islanding detection scheme is based on superimposed positive sequence impedance (SPSI). For calculating the superimposed positive sequence impedance (SPSI), the voltage and current signals are obtained from targeted DG points. The scheme’s performance is tested on multiple bus systems across islanding and non-islanding conditions using a MATLAB/Simulink environment. It is shown that even in the presence of noise, the algorithm can determine an islanding decision with high accuracy and a short detection time of 84 ms. In comparison to other algorithms, it operates at zero power mismatch (ZPM) and does not affect power quality.

Genomic surveillance of malaria parasites in an indigenous community in the Peruvian Amazon

Hard-to-reach communities represent Peru's main challenge for malaria elimination, but information about transmission in these areas is scarce. Here, we assessed Plasmodium vivax (Pv) and P. falciparum (Pf) transmission dynamics, resistance markers, and Pf hrp2/3 deletions in Nueva Jerusalén (NJ), a remote, indigenous community in the Peruvian Amazon with high population mobility. We collected samples from November 2019 to May 2020 by active (ACD) and passive case detection (PCD) in NJ. Parasites were identified with microscopy and PCR. Then, we analyzed a representative set of positive-PCR samples (Pv = 68, Pf = 58) using highly-multiplexed deep sequencing assays (AmpliSeq) and compared NJ parasites with ones from other remote Peruvian areas using population genetics indexes. The ACD intervention did not reduce malaria cases in the short term, and persistent malaria transmission was observed (at least one Pv infection was detected in 96% of the study days). In Nueva Jerusalen, the Pv population had modest genetic diversity (He = 0.27). Pf population had lower diversity (He = 0.08) and presented temporal clustering, one of these clusters linked to an outbreak in February 2020. Moreover, Pv and Pf parasites from NJ exhibited variable levels of differentiation (Pv Fst = 0.07–0.52 and Pf Fst = 0.11–0.58) with parasites from other remote areas. No artemisin resistance mutations but chloroquine (57%) and sulfadoxine-pyrimethamine (35–67%) were detected in NJ's Pf parasites. Moreover, pfhrp2/3 gene deletions were common (32–50% of parasites with one or both genes deleted). The persistent Pv transmission and the detection of a Pf outbreak with parasites genetically distinct from the local ones highlight the need for tailored interventions focusing on mobility patterns and imported infections in remote areas to eliminate malaria in the Peruvian Amazon.

Space-Based Passive Orbital Maneuver Detection Algorithm for High-Altitude Situational Awareness

Orbital maneuver detection for non-cooperative targets in space is a key task in space situational awareness. This study develops a passive maneuver detection algorithm using line-of-sight angles measured by a space-based optical sensor, especially for targets in high-altitude orbit. Emphasis is placed on constructing a new characterization for maneuvers as well as the corresponding detection method. First, the concept of relative angular momentum is introduced to characterize the orbital maneuver of the target quantitatively, and the sensitivity of the proposed characterization is analyzed mathematically. Second, a maneuver detection algorithm based on the new characterization is designed in which sliding windows and correlations are utilized to determine the mutation of the maneuver characterization. Subsequently, a numerical simulation system composed of error models, reference missions and trajectories, and computation models for estimating errors is established. Then, the proposed algorithm is verified through numerical simulations for both long-range and close-range targets. The results indicate that the proposed algorithm is effective. Additionally, the sensitivity of the proposed algorithm to the width of the sliding window, accuracy of the optical sensor, magnitude and number of maneuvers, and different relative orbit types is analyzed, and the sensitivity of the new characterization is verified using simulations.

Research on a new method of islanding detection based on lifting wavelet and neural network

Abstract At present, the commonly used active and passive islanding detection methods have their own shortcomings, and the islanding detection effect is difficult to meet the requirements. Therefore, a new detection method based on wavelet signal processing and artificial intelligence to identify islanding is proposed in this paper. In this method, the feature quantities required for islanding detection are obtained by wavelet transform and signal processing, and then the feature quantities are identified by neural network to determine whether the islanding is generated in distributed generation system. Wavelet transformation has a strong ability of signal feature extraction, while the neural network has strong learning and identification abilities, the combination of the both is beneficial to improve the success rate of islanding detection. Simulation verification shows that the new islanding detection method proposed in this paper can detect islanding quickly and accurately, and the performance of islanding detection has been significantly improved.

Microwave irradiation-induced deterioration of rock mechanical properties and implications for mechanized hard rock excavation

In this study, a novel microwave-water cooling-assisted mechanical rock breakage method was proposed to address the issues of severe tool wear at elevated temperatures, poor rock microwave absorption, and excessive microwave energy consumption. The investigation object was sandstone, which was irradiated at 4 kW microwave power for 60 s, 180 s, 300 s, and 420 s, followed by air and water cooling. Subsequently, uniaxial compression, Brazilian tension, and fracture tests were conducted. The evolution of damage in sandstone was measured using active and passive nondestructive acoustic detection methods. The roughness of the fracture surfaces of the specimens was quantified using the box-counting method. The damage mechanisms of microwave heating and water cooling on sandstone were discussed from both macroscopic and microscopic perspectives. The experimental results demonstrated that as the duration of the microwave irradiation increased, the P-wave velocity, uniaxial compressive strength (UCS), elastic modulus (E), tensile strength, and fracture toughness of sandstone exhibited various degrees of weakness and were further weakened by water cooling. Furthermore, an increase in the microwave irradiation duration enhanced the damaging effect of water cooling. The P-wave velocity of the sandstone was proportional to the mechanical parameters. Microwave heating and water cooling weakened the brittleness of the sandstone to a certain extent. The fractal dimension of the fracture surface was correlated with the duration of microwave heating, and the water-cooling treatment resulted in a rougher fracture surface. An analysis of the instantaneous cutting rate revealed that water cooling can substantially enhance the efficiency of microwave-assisted rock breakage.

Passive Detection of a Random Signal Common to Multi-Sensor Reference and Surveillance Arrays

Passive Detection of a Random Signal Common to Multi-Sensor Reference and Surveillance Arrays

Monitoring holograms for therapeutic ultrasound using passive cavitation beamforming

Acoustic holograms can generate cavitation patterns of complex spatial distribution by shaping and steering the focal spot of therapeutic ultrasound systems. However, when monitoring these systems by passive cavitation detection, off-axis therapeutical targets and the receiver directivity may not be aligned. In this paper, we present passive cavitation beamforming to monitor a therapeutical ultrasound system using holograms targeted to arbitrary locations, in which both therapeutic and passive cavitation monitoring systems use 3D-printed acoustic lenses. The therapeutic system uses an acoustic hologram to focus the ultrasound beam on the target, which is off-axis. Then, a second lens is designed to beamform the cavitation signals which emerge from the therapeutic target, steering the directivity of the passive cavitation detector in the direction of the therapeutic focus and, in addition, compensating for skull aberrations. The system is experimentally tested with an ex-vivo macaque skull and a blood vessel phantom with microbubbles. In addition, results are compared with a standard confocal configuration and an off-axis configuration in the absence of the monitor lens. A parametric study is performed by varying the amplitude of the emitted signal and the impact on the behaviour of the microbubbles is analysed based on the cavitation index values. Results show that monitoring holograms align the passive cavitation detector response with the focal spot of the targeted therapeutic transducer. These holograms encode a fixed beamformer for cavitation signals in reception, increasing the sensitivity of cavitation emission at the target. In this way, cavitation doses can be used to locally monitor the cavitation activity of microbubbles, thus opening a new path to low-cost monitoring of therapeutic ultrasound systems.

О поиске источников шума группой взаимодействующих АНПА с применением генетического алгоритма

Marine unmanned systems are increasingly used in tasks related to search and observation missions. Protection of water areas, survey and inspection operations, tracking of marine animals are examples of such missions. Most of these tasks can be solved more efficiently by use a group of interacting marine drones, compared to single vehicle. The article considers the problem of passive detection and localization of noise objects in a given water area by use a group of autonomous underwater vehicles (AUV). It is assumed that antennas of scalar vector receivers are installed on board the AUV to detect and determine the direction to the noise source. Some ways of organizing the group work of such AUV are considered. A centralized version is investigated, when the collected current information from all AUV is transmitted to one AUV leader. On the base of received information processing, AUV leader forms a group work plan, including the motion parameters for all AUV, to detect and determine the location of noise sources. An approach based on the use of a genetic algorithm is considered, and several versions of its implementation are investigated. The results of model experiments are presented, which demonstrate the efficiency of the proposed algorithms.

Fast Algorithm of Passive Bistatic Radar Detection Based on Batches Processing of Sparse Representation and Recovery

In the passive bistatic radar (PBR) system,methods exist to address the issue of detecting weak targets without being influenced by non-ideal factors from adjacent strong targets. These methods utilize the sparsity in the delay-Doppler domain of the cross ambiguity function (CAF) to detect weak targets. However, the modeling and solving of this method involve substantial memory consumption and computational complexity. To address these challenges, this paper establishes a target detection model for PBR based on batch processing of sparse representation and recovery. This model partitions the CAF into blocks, identifies blocks requiring processing based on the presence of targets, and improves the construction and utilization of the measurement matrix. This results in a reduction in the computational complexity and memory resource requirements for sparse representation and recovery, and provides favorable conditions for parallel execution of the algorithm. Experimental results indicate that the proposed approach increases the number of blocks by a factor of four, and reduces the number of real multiplications by approximately an order of magnitude. Hence, compared with the traditional approach, the proposed approach enables fast and stable detection of weak targets.

Method for improving the positional accuracy in passive optical detection of space objects

The number of space objects, i.e., active satellites as well as space debris, is growing at an exponential rate. The management of congested space requires networks of sensors to detect and precisely measure the positions of objects in space. We describe a method that improves the positional accuracy of passive optical detection of space objects. The method is based on a laboratory sensor calibration, which is suitable for all types of cameras (CCD and CMOS cameras) and can easily be implemented for existing staring or tracking stations or even used with space-based passive optical sensors. The successful implementation of the method is demonstrated in a test campaign by measuring tracklets of several Earth-orbiting satellites with a ground-based staring system known as APPARILLO. In addition to its use in space object detection, we encourage that the presented method might also inspire other fields of research and technology, where images need to be acquired with precise timing.

Prognostics of multiple malaria episodes and nutritional status in children aged 6 to 59 months from 2013 to 2017 in Dangassa, Koulikoro region, Mali

BackgroundIn Africa, the relationship between childhood nutritional status and malaria remains complex and difficult to interpret. Understanding it is important in the improvement of malaria control strategies. This study aimed to assess the influence of nutritional status on the occurrence of multiple malaria episodes in children aged 6 to 59 months between 2013 and 2017 living in the village of Dangassa, Mali.MethodsA community-based longitudinal study was conducted using cross-sectional surveys (CSSs) at the beginning (June) and end (November) of the malaria transmission season associated with passive case detection (PCD) at the Dangassa Community Health Centre. Children with asymptomatic malaria infection during cross-sectional surveys were selected and their malaria episodes followed by PCD. Malaria indicators in person-months were estimated using an ordinal-logistic model repeated on subjects during follow-up periods.ResultsThe incidence rate (IR) during the period of high transmission (June to October), for 1 episode and for 2 + episodes peaked in 2013 with 65 children (IR = 95.73 per 1000 person-months) and 24 cases (IR = 35.35 per 1000 person-months), respectively. As expected, the risk of multiple episodes occurring during the period of high transmission was 3.23 compared to the period of low transmission after adjusting for other model parameters (95% CI [2.45–4.26], p = 0.000). Children with anaemia were at high risk of having multiple episodes (OR = 1.6, 95% CI [1.12–2.30], p = 0.011). However, the risk of having 2 + episodes for anemic children was higher during the period of low transmission (RR = 1.67, 95% CI [1.15–2.42], p = 0.007) compared to the period of high transmission (RR = 1.58, 95% CI [1.09–2.29], p = 0.016). The trend indicated that anemic and underweight children were significantly associated with multiple malaria episodes during the period of low transmission (p < 0.001).ConclusionResults show that multiple episodes of malaria are significantly related to the nutritional status (anaemia and underweight) of the child during the two transmission seasons and more pronounced during the dry season (period of low transmission). Further research including other malnutrition parameters will be needed to confirm these findings.