Arrival Of Signals Research Articles

Parameter Estimation of Frequency-Hopping Signal in UCA Based on Deep Learning and Spatial Time–Frequency Distribution

The parameter estimation and sorting of frequency-hopping (FH) signals are of great importance in both civilian and military applications. In this article, the estimation of hopping time, hopping period, hopping frequency, instantaneous bandwidth, and 2-D direction of arrival (2-D-DOA) of multiple FH signals in the uniform circular array (UCA) is studied. First, a novel lightweight model based on You Only Look Once (YOLO), named FH-GYOLO, is proposed to detect FH signals and estimate their time–frequency (TF) parameters. The proposed FH-GYOLO takes advantage of the ghost module, which can significantly reduce the computational cost and, simultaneously, achieve an efficient detection with high performance. Then, the 2-D-DOA estimation method of FH signals in UCA is proposed with the spatial TF distribution (STFD). In the proposed method, the steering vector of UCA and the STFD matrix are transformed into beamspace by beamspace transformation, and the closed-form solution is derived for the estimation of autopaired elevation and azimuth angles without the computationally expensive spatial–spectral search. Furthermore, in the proposed method, an iterative compensation process is developed, which can greatly improve the accuracy of DOA estimation without significantly increasing the computational complexity. Extensive simulation results and analysis demonstrated that the proposed algorithms exhibit better or similar performance than the other benchmark methods, and most importantly, the computational cost is substantially reduced.

Monte Carlo modelling for elastic and Raman signals in oceanic LiDAR.

We investigate Raman returns in oceanic light detection and ranging (LiDAR), and explore the similarities and differences to conventional elastic returns. We show that Raman returns have much more complex behavior than elastic returns, which likely cannot be well matched by simple models, making Monte Carlo simulations essential. We investigate the correlation between the time of signal arrival and the depth of the Raman event, and find that a linear correlation only exists for judicious choice of system parameters.

Photonic system for Doppler-frequency-shift and Angle-of-arrival simultaneous measurement using dual-parallel Mach–Zehnder modulator

A simple photonic system is proposed to measure the Doppler frequency shift (DFS) and Angle of arrival (AOA) of microwave signals simultaneously. The echo signals received by the two antennas are fed into two sub-MZM of a dual-parallel Mach–Zehnder modulator (DPMZM) respectively, and the reference signals are sent into one of the sub-MZM. The introduction of reference signals makes it easier to determine the direction of DFS. After the reference signal and echo signal pass through the low-speed PD, the beating signal is obtained. The value and direction of the DFS can be derived from the frequency of the down-converted signal. And the measurement of AOA can be calculated from the power of the output signal. The experimental results show that the echo signal measurement errors of DFS are less than ±0.5 Hz in the operating frequency range of 20 GHz, and the power sensitivity is less than -40 dBm. AOA has measurement errors of less than ±1.5° in the range of 0 to 90°. In addition, by adding only one test branch, the system can achieve the unambiguous measurement of AOA in the range of ±90°.

ФОРМИРОВАНИЕ СТРУКТУРНОЙ СХЕМЫ РАДИООБМЕНА С ПРИМЕНЕНИЕМ ПСП

The structure of the radio exchange demonstrates the interconnection pattern of the drones with the control center. To protect against unauthorized access to control and navigation channels it is necessary to hide such data and increase their noise immunity. The aim of the work is to use signals with a pseudorandom sequence and duplicate control and navigation blocks in the information channel of a small-scale aerial vehicle. Thus, at the beginning of the paper, a general structural diagram of radio communication between the unmanned aerial vehicle and the control center is presented. The model of 2-element antenna array consisting of two non-directional antenna elements is considered. On the basis of which it is possible to conclude about the signal arrival with a phase shift, taking into account which it is possible to determine the output signal of the array. An important factor is the synchronization and encryption of the signal. Data synchronization can be used by synchronous signal transmission between the drone and the control center. To reduce the probability of interception of the synchronous signal, the data packets containing it are transmitted in a pseudo-random sequence. Synchronization is achieved by using a micronavigation system through continuous radio transmissions from a ground source and simultaneous reception and recording of the signal on the drone. A one-time encryption or scrambler with a reversible symmetric transformation of the encoded information can be used as an encryption or scrambler. A random number generator is used to generate a sequence of random data, from which an array of key information tied to a specific period of use is created. The phase method can be used to process the signal. By measuring the phase shift with a phase detector, you can determine the location of the radio source with respect to the base normal. Measurements can be made with a digital receiving antenna array. Signal processing with digital receiving antenna array is performed by the diagramming device and the adaptive processor unit. As a result, all data using this approach is entered into the information block with the use of a pseudo-random coding change scheme, pseudo-random permutation of the navigation and control blocks.

Direction of arrival estimation using two-dimensional microphone arrays

Many signal processing applications require knowledge of where sources are located relative to the receiver. In cases where the source locations are not known in advance, methods must be implemented to estimate the direction of arrival (DOA) of the incoming signals. This paper proposes a method for estimating the DOA of acoustic signals in real time using a two-dimensional array of microphones. While many existing methods focus solely on obtaining an accurate estimate of one or more sound sources, the proposed method aims to provide a more complete picture of the sound field measured by the microphone array. This method can be easily adapted to identify and track any number of independent sources without a significant increase in either complexity or computational expense, making it suitable for applications where very little about the sound field can be known in advance.

State-Space Model for Arrival Time Simulations and Methodology for Offline Blade Tip-Timing Software Characterization

Blade tip-timing is an extensively used technique for measuring blade vibrations in turbine and compressor stages; it is one of the preferred techniques used for characterizing their dynamic behaviors using non-contact probes. Typically, arrival time signals are acquired and processed by a dedicated measurement system. Performing a sensitivity analysis on the data processing parameters is essential for the proper design of tip-timing test campaigns. This study proposes a mathematical model for generating synthetic tip-timing signals, descriptive of specific test conditions. The generated signals were used as the controlled input for a thorough characterization of post-processing software for tip-timing analysis. This work represents the first step in quantifying the uncertainty introduced by tip-timing analysis software into user measurements. The proposed methodology can also offer essential information for further sensitivity studies on parameters that influence the accuracy of data analysis during testing.

Tackling the challenges of tectonic tremor localization using differential traveltimes and Bayesian inversion

SUMMARY Episodic tremor and slip events in Northern Cascadia produce low-frequency, emergent seismic signals, often referred to as tectonic tremor. Methods designed to locate tremor face two challenges that increase the likelihood of producing low quality catalogues: first, signal arrival and duration are often poorly defined; second, high rates of tremor activity during episodes can cause multiple signals to be indiscernible from each other. In this paper, we present a new method of locating tectonic tremor using differential traveltimes from a waveform-envelope cross-correlation in a grid-based Bayesian inversion. To address the aforementioned challenges, we use a recently developed three-dimensional shear wave velocity model to compute traveltimes, and include processes to remove data outliers, estimate data error statistics, and quantify uncertainties within the Bayesian framework. Although this method is designed for tremor, to test the approach we consider a set of 58 local earthquakes between magnitudes −0.07 and 2.6 in the Southern Vancouver Island region and obtain well-constrained relocations. Residuals between official catalogue values and our relocations are quantized with respect to the 1 km grid resolution of the inversion, and average 2.7 km in epicentre and 5.2 km in depth. Analysis shows that depths of relocations are sensitive to horizontal variations and simplifications in velocity models. We then present our catalogue of tremor events during the 2004 episodic tremor and slip event beneath Southern Vancouver Island, Canada. Median uncertainties of tremor events quantified by 95 per cent credibility interval widths in a 1 km grid are 5 km and 9.km in horizontal and depth directions, respectively (1.2 km and 2.3 km using traditional standard deviation-based uncertainties). Comparison of our catalogue with previously published work demonstrates that our new method yields a good detection rate, a greater degree of epicentral clustering, and better depth resolution of tremor events. Catalogues produced using this new method may help to provide insight into the spatial extent of tremor, especially in depth, by yielding enhanced constraints on source locations on a regional scale.

Centroid Optimization of DNN Classification in DOA Estimation for UAV

Classifications based on deep learning have been widely applied in the estimation of the direction of arrival (DOA) of signal. Due to the limited number of classes, the classification of DOA cannot satisfy the required prediction accuracy of signals from random azimuth in real applications. This paper presents a Centroid Optimization of deep neural network classification (CO-DNNC) to improve the estimation accuracy of DOA. CO-DNNC includes signal preprocessing, classification network, and Centroid Optimization. The DNN classification network adopts a convolutional neural network, including convolutional layers and fully connected layers. The Centroid Optimization takes the classified labels as the coordinates and calculates the azimuth of received signal according to the probabilities of the Softmax output. The experimental results show that CO-DNNC is capable of acquiring precise and accurate estimation of DOA, especially in the cases of low SNRs. In addition, CO-DNNC requires lower numbers of classes under the same condition of prediction accuracy and SNR, which reduces the complexity of the DNN network and saves training and processing time.

Photonics-Based Simultaneous DFS and AOA Measurement System without Direction Ambiguity

A novel scheme that can simultaneously measure the Doppler frequency shift (DFS) and angle of arrival (AOA) of microwave signals based on a single photonic system is proposed. At the signal receiving unit (SRU), two echo signals and the reference signal are modulated by a Sagnac loop structure and sent to the central station (CS) for processing. At the CS, two low-frequency electrical signals are generated after polarization control and photoelectric conversion. The DFS without direction ambiguity and wide AOA measurement can be real-time acquired by monitoring the frequency and power of the two low-frequency electrical signals. In the simulation, an unambiguous DFS measurement with errors of ±3 × 10-3 Hz and a -90° to 90° AOA measurement range with errors of less than ±0.5° are successfully realized simultaneously. It is compact and cost-effective, as well as has enhanced system stability and improved robustness for modern electronic warfare systems.

Self-Calibration Method of Sensors Array Errors Based on Rotation Measurement

Array calibration is the premise of successful array signal processing. The active calibration needs to know the direction of arrival (DOA) of calibration source signals accurately; otherwise, the performance will deteriorate. Although the conventional self-calibration does not need accurate DOA of calibration sources, it may suffer from falling into the local extremum since there are too many parameters to be estimated. Thus, we propose a novel self-calibration method based on the rotation measurement. The rotation measurement is that the array receives signals from a fixed source with different array rotation angles. The proposed method jointly estimates array errors and DOAs of the sources by an alternative minimization (AM) algorithm. Through the derivation of a suitable initial value in the AM algorithm, we could improve the robustness and reduce the computational complexity. The proposed method can achieve as high calibration accuracy as the active method even if there is an error in the source DOA information and can apply to arbitrary planar arrays. Both simulation and field experiment results demonstrate the effectiveness of the proposed method.

Optimization of Basepoint Configuration in Localization of Signal Interference Device

Precise navigation, as a method for guiding vehicles from one point to another, is an important subject these days especially in navigation of aircraft. Global navigation satellite systems (GNSSs) are capable tools for such a purpose. Any intentional or unintentional interference in satellite signals may cause risks of deadly accidents. Therefore, it is tremendously important to control airports or harbors and locate any existing radio frequency interference device. This localization can be done based on measuring time of arrival (TOA), angle of arrival (AOA), or time difference of arrival (TDOA) of signals from the device to sensors or receivers at some basepoints. In this article, a method is proposed based on these arrivals for optimizing the configuration created by these basepoints from a large grid of points covering a control area. Furthermore, a simulation test was performed to verify the theory, and after that a control network was designed and optimized for the international Landvetter Airport of Sweden. Our simulation studies show that when the AOA is used, our optimization is more robust with respect to the control grid resolution. In addition, optimization based on the TDOA improves the coverage over the control area with a significant reduction of error of control points, but because of the special geometric shape of the Landvetter Airport, such an optimization was not successful.

A new method of retrieving atmospheric refractivity structure

ABSTRACT It is proposed to obtain information on atmospheric refractivity structure by measuring the angle of arrival (AoA) of radio signals routinely broadcast by commercial aircraft. The angle of arrival would be measured at hill-top sites using a simple two-element interferometer. Knowledge of the aircraft’s location (information conveniently contained within the broadcasts) and the AoA will enable the bending angle of the signals to be calculated. As measurable bending will only occur at grazing incidence, sources of signals either very close to the radio horizon, or at a similar height to the interferometer, are essential. The routine navigational data broadcasts from civil aircraft represent the ideal source. In areas of high air traffic density such as the UK, ~-bending angle measurements may be possible each day. Numerical weather prediction models routinely assimilate bending angles retrieved from GNSS radio occultation data, so it is anticipated that assimilation methods could be developed that are able to make good use of this new source of bending angle data. Sensitivity tests were performed to estimate the resolution of humidity retrievals assuming a target AoA accuracy of 0.01°. Simulated annealing was used to demonstrate the ability to retrieve relative humidity and mixing ratio vertical profiles using AoA measurements. It is shown that for observed AoA measurements with an accuracy of 0.01° it should be possible to retrieve relative humidity and mixing ratio vertical profiles with an accuracy of ~ and ~ g/kg respectively. An AoA accuracy of 0.01° should be achievable using hardware costing ~€10k, however further hardware development is still required.

Fast and Accurate Single-Snapshot DOA Estimation: Iterative Interpolated Approaches

Estimating the Direction of Arrival (DOA) of a single source signal from a single observation of an array data still plays an important part in practical application scenarios. To address the problem, this letter proposes two iterative, fast and accurate approaches namely Q-Shift based DOA Estimation Algorithm (QS-DOAEA) and Tradeoff between A&M and Q-Shift based DOA Estimation Algorithm (TAQ-DOAEA). QS-DOAEA adopts the interpolation of shifted DFT coefficients to iteratively obtain the near-optimal estimation. TAQ-DOAEA employs the error function by simultaneously mixing the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -shifted and half-shifted DFT coefficients, which only requires two iterations. Numerical results reveal that QS-DOAEA achieves significant improvement in terms of estimation accuracy and TAQ-DOAEA expedites the convergence. The proposed estimation algorithms demonstrate that they have an asymptotic variance that is at least 1.0013 times asymptotic Cramér-Rao bound (ACRB), and provide more than 80× reduction in the computational cost, compared to the baseline method. All our proposed algorithms and code are available at https://github.com/jn-z/.

Exploiting Phase Difference of Arrival of V2X Signals for Pedestrian Positioning: Key Methods and Simulation Evaluation

Exploiting Phase Difference of Arrival of V2X Signals for Pedestrian Positioning: Key Methods and Simulation Evaluation

Угловое разрешение сигналов в многобазовых фазовых пеленгаторах

Angular resolution method of signal sources in phase direction finders with antenna systems in the form of linear, flat or three-dimensional arrays consisting of weakly directed elements is considered. The angular resolution of the signals is achieved by determining for each of the sources its own set of full periods of phase differences lost during measurements. It is shown that the maximum likelihood method developed for estimating the angle of arrival of a single signal is suitable for angular resolution of signals. There is given the received signals bearing angle accuracy evaluation.

Long Baseline Acoustic Localization Based on Track-Before-Detect in Complex Underwater Environments

This paper considers the long baseline (LBL) acoustic localization problem. For this problem, traditional two-step localization methods first estimate the time of arrivals (TOAs) of the target signal and then solve the target’s position based on the estimated TOAs. Since TOA estimation is performed at each buoy independently, they are suboptimal without considering the physical basis that the TOAs estimated from different buoys all correspond to the same target position. To overcome this drawback, we propose a novel localization approach based on track-before-detect (TBD) and particle filtering (PF) theory, which directly determines the target’s position. Since this method breaks from the traditional two-step paradigm, several extra challenges arising from the two-step paradigm itself can be avoided. Specifically, we make two main contributions. First, a unique method is given for designing the likelihood function of the PF framework, which defines the likelihood function as the product of the matched filter outputs of multiple buoys conditioned on the particle states. As this design scheme is without any assumptions on the emission signal type, it can be applied to any signal type. Second, multiple models are employed to sample the particles to reduce the performance loss caused by target maneuvers. Additionally, an auxiliary variable is used to improve the sampling efficiency of the multiple models. The efficacy of the proposed method is demonstrated both in simulations and on real datasets. Experimental results show that the proposed algorithm outperforms the traditional LBL localization methods under harsh conditions.

On trailing waves rather than lamb waves being generated by buried in-plane dipoles in thick plates

The potential for trailing waves (TWs) rather than Lamb waves to be observed in the out-of-plane displacement signals from acoustic emission (AE) sources in thick plates was examined. Finite element modeling (FEM) was done for buried in-plane dipole (IPD) sources in steel plates with thicknesses up to 125 mm and propagation distances from 250 mm to 1500 mm. The domain was large enough so that significant reflections were not observed during the primary signal arrivals. The run times extended to 1 ms. “Ring-type” sources were used so that axisymmetric modeling could be done. The rise time of the IPDs was typically 1 μs with a cosine-bell time dependence, and the two 1 N forces were spaced by 200 μm. The IPDs were located at several depths from very near the top surface of the plates to the midplane. The displacements as a function of time were obtained on both the top and bottom surfaces. The analysis primarily considered a bandpass of 80 kHz to 500 kHz. In addition, fast Fourier transform results and time/frequency analysis were used. The typical character of TWs consisted of a train of short wave-packets (each 10 to 25 microseconds). The significant-amplitude TW packets arrived after an arrival time corresponding to the Rayleigh wave velocity. The number of packets in the train increased with increasing propagation distance. The likelihood of the signals exhibiting TWs increased with increases in plate thickness, increases in the distance of the IPD below the surface of interest. The presence of the TWs complicates the determination of fixed velocity arrival times necessary for source location determination. Also, since TWs rather than Rayleigh waves appear for IPD depths at some distance below the surface used to sense AE signals, there are potential issues when the AE approach depends on a Rayleigh wave being present.

DOA Signal Identification Based on Amplitude and Phase Estimation for Subarray MIMO Radar Applications

The overlapped equal subarray transmit radar, which is also known as the Subarray Multiple-Input Multiple-Output radar, utilizes the key advantages simultaneously of both types of multi-antenna radar, i.e. the phased array and MIMO radars, so that it is able to detect multiple targets even though it has a radar cross section (RCS) of a weak or small target. In this paper, it is proposed to develop a parameter estimation approach called amplitude and phase estimation (APES). This approach provides improved resolution to the estimation of the amplitude and direction of arrival (DoA) of the target reflection signal on the radar compared to the existing conventional estimation methods such as least squares (LS). The formulation of the APES method on this radar is based on the tested parameters such as DoA and RCS and continuously being evaluated. The results show that the performance of the APES method of this radar can detect targets very precisely when the number of subarrays (M) is greater than the number of detection targets (P), precisely M &gt; P. For the results of DoA and RCS accuracy from the APES method, this radar is more accurate than the LS when testing the angular resolution between the two targets, an angle resolution of 2° is obtained for the APES method which is superior to the LS with an angle resolution of 5.8°. In these conditions, the APES method is able to accurately distinguish between two targets while the LS method is only able to detect one target.

Direction-of-Arrival Estimation Based on Frequency Difference-Wavenumber Analysis for Sparse Vertical Array Configuration.

Frequency-wavenumber (f-k) analysis can estimate the direction of arrival (DOA) of broadband signals received on a vertical array. When the vertical array configuration is sparse, it results in an aliasing error due to spatial sampling; thus, several striation patterns can emerge in the f-k domain. This paper extends the f-k analysis to a sparse receiver-array, wherein a multitude of sidelobes prevent resolving the DOA estimates due to spatial aliasing. The frequency difference-wavenumber (Δf-k) analysis is developed by adopting the concept of frequency difference, and demonstrated its performance of DOA estimation to a sparse receiver array. Experimental results verify the robustness of the proposed Δf-k analysis in the estimation of the DOA of cracking sounds generated by the snapping shrimps, which were recorded by a sparse vertical array configuration during the shallow water experiment.

Direction Finding for Passive Bistatic Radar in the Presence of Multipath Propagation

In the case of multipath propagation for passive bistatic radar (PBR) using uncooperative frequency agile-phased array radar as an illuminator, a new direction-finding method is proposed to deal with the scenario where the coherent and uncorrelated signals are closely spaced or in the same direction. Firstly, spatial difference technique is used to eliminate uncorrelated signals. Then, in order to avoid the cross-terms effect and improve the resolution of coherent signal, the iterative adaptive method (IAA) is adopted for the rearranged spatial difference matrix. Finally, the direction of arrival (DOA) of the target signal is obtained by the reconstruction of the interference-plus-noise covariance matrix. Compared with previous studies, this method has better performance in the case of low signal-to-noise ratio (SNR) and limited number of snapshots.