Coherent Signals Research Articles

Performance of Galileo satellite products determined from multi-frequency measurements

Each Galileo satellite provides coherent navigation signals in four distinct frequency bands. International GNSS Service (IGS) analysis centers (ACs) typically determine Galileo satellite products based on the E1/E5a dual-frequency measurements due to the software limitation and the limited tracking capability of other signals in the early time. The goal of this contribution is to evaluate the quality of Galileo satellite products determined by using different dual-frequency (E1/E5a, E1/E5b, E1/E5, E1/E6) and multi-frequency (E1/E5a/E5b/E5/E6) measurements based on different sizes of ground networks. The performance of signal noise, the consistency of frequency-specific satellite phase center offsets and the stability of satellite phase biases are assessed in advance to confirm preconditions for multi-frequency processing. Orbit results from different dual-frequency measurements show that orbit precision determined from E1/E6 is clearly worse (about 35%) than that from other dual-frequency solutions. In view of a similar E1, E5a, E5b and E6 measurement quality, the degraded E1/E6 orbit performance is mainly attributed to the unfavorable noise amplification in the respective ionosphere-free linear combination. The advantage of using multi-frequency measurements over dual-frequency for precise orbit determination is clearly visible when using small networks. For instance, the ambiguity fixing rate is 80% for the multi-frequency solution while it is less than 40% for the dual-frequency solution if 150 s data sampling is employed in a 15-station network. Higher fixing rates result in better (more than 30%) satellite orbits and more robust satellite clock and phase bias products. In general, satellite phase bias products determined from a 20-station (or more) network are precise enough to conduct precise point positioning with ambiguity resolution (PPP-AR) applications. Multi-frequency kinematic PPP-AR solutions always show 5–10% precision improvement compared to those computed from dual-frequency observations.

Direction finding by sparse‐based approach for dual‐polarised conformal array in the presence of gain and phase uncertainties

AbstractThis article investigates the problem of robust direction‐of‐arrival (DOA) estimation with unknown sensor gain and phase uncertainties. A Dual‐Polarised Regularised Multiple FOCal Underdetermined System Solver is proposed to estimate the 2‐D DOA for the dual‐polarised conformal array. Each polarisation signal is decomposed into two orthogonal components, which are regarded as a pair of coherent signals, and the polarisation parameters are merged into the signal waveform. A sparse‐based method based on the coherent signals block is presented, implementing weight sharing and grid pruning within the block to alleviate the negative influence of the errors. Meanwhile, gain and phase errors are modelled as the equivalent noise, which can be suppressed with the adaptive adjustment for the regularisation parameter. As the insensitivity of the sparse‐based algorithm to coherent signals, the proposed algorithm can realise the blind polarisation 2‐D DOA estimation. The Cramer–Rao bound is derived, and simulations exhibit the effectiveness and robustness of the proposed method with the unknown sensor gain and phase uncertainties.

High-Resolution NMR Spectroscopy at Large Fields with Nitrogen Vacancy Centers.

Ensembles of nitrogen-vacancy (NV) centers are used as sensors to detect nuclear magnetic resonance signals from micron-sized samples at room temperature. In this scenario, the regime of large magnetic fields is especially interesting as it leads to a large nuclear thermal polarization-thus, to a strong sensor response even in low concentration samples-while chemical shifts and J couplings become more accessible. Nevertheless, this regime remains largely unexplored owing to the difficulties of coupling NV-based sensors with high-frequency nuclear signals. In this Letter, we circumvent this problem with a method that maps the relevant energy shifts in the amplitude of an induced nuclear spin signal that is subsequently transferred to the sensor. This stage is interspersed with free-precession periods of the sample nuclear spins where the sensor does not participate. Thus, our method leads to high spectral resolutions ultimately limited by the coherence of the nuclear spin signal.

A Deep Learning Approach to Detect Failures in Bridges Based on the Coherence of Signals

Structural health monitoring of civil infrastructure, such as bridges and buildings, has become a trending topic in the last few years. The key factor is the technological push given by new technologies that permit the acquisition, storage, processing and visualisation of data in real time, thus assessing a structure’s health condition. However, data related to anomaly conditions are difficult to retrieve, and, by the time those conditions are met, in general, it is too late. For this reason, the problem becomes unsupervised, since no labelled data are available, and anomaly detection algorithms are usually adopted in this context. This research proposes a novel algorithm that transforms the intrinsically unsupervised problem into a supervised one for condition monitoring purposes. Considering a bridge equipped with N sensors, which measure static structural quantities (rotations of the piers) and environmental parameters, exploiting the relationships between different physical variables and determining how these relationships change over time can indicate the bridge’s health status. In particular, this algorithm involves the training of N models, each of them able to estimate the quantity measured via a sensor by using the others’ N−1 measurements. Hence, the system can be represented by the ensemble of the N models. In this way, for each sensor, it is possible to compare the real measurement with the predicted one and evaluate the residual between the two; this difference can be addressed as a symptom of changes in the structure with respect to the condition regarded as nominal. This approach is applied to a real test case, i.e., Candia Bridge in Italy, and it is compared with a state-of-the-art anomaly detector (namely an autoencoder) in order to validate its robustness.

Entangled Frequency-Tunable Microwave Photons in a Superconducting Circuit

We propose a frequency-tunable source to emit entangled microwave photons on the platform of a superconducting circuit, in which two superconducting transmission-line resonators are coupled via a capacitor and one resonator is inserted with a superconducting quantum interference device (SQUID) in the center. By pumping the circuit appropriately with an external coherent microwave signal through the SQUID, microwave photons are emitted in pairs out of the circuit. The entanglement between the two modes is demonstrated by numerically calculating the second-order coherence function and the logarithmic negativity of the output microwave signals. Due to the tunability of SQUID’s equivalent inductance, the frequencies of the entangled microwave photons can be tuned by an external flux bias in situ. Our proposal paves a new way for obtaining entangled frequency-tunable two-mode microwave photons.

L0 Regularization parameter for sparse DOA estimation of coherent signals with modeling errors

Sparse methods have been recently introduced in Direction-Of-Arrival (DOA) estimation as an alternative to subspace-based methods and Maximum Likelihood (ML) techniques. This paper proposes a low complexity sparse L0-regularized method for DOA estimation of coherent signals in multipath environment, a scenario in which subspace-based methods fail. The first eigenvector of the covariance matrix is used as an observation and its statistics in the presence of modeling errors are derived. Thanks to those statistics, we present a theoretical statistical analysis of an interval in which the regularization parameter, usually empirically tuned, should stand. For a regularization parameter in this interval, the global solution of the L0-regularized problem coincides with the solution of the deterministic ML. An off-line selection of the regularization parameter is therefore proposed. Simulations confirm the relevance of this interval and of the proposed method.

Mitigating nonlinear penalty induced from a low-speed optical supervisory channel on coherent signals.

With the increasing signal rates of a long-haul backbone dense-wavelength-division-multiplexing (DWDM) transmission system, e.g., from 100 Gb/s to 400 Gb/s and even to 800 Gb/s, optical path impairments simultaneously become more severe. Harmful factors being formerly insignificant become noticeable, e.g., nonlinear phase noise (NPN) on main DWDM channels induced by the cross-phase modulation (XPM) from the low-speed optical supervisory channel (OSC). Field trials show that a greater than 5.13-dB penalty can be observed on the shortest channel of 400G DP-16QAM-PCS over G.654.E links, which greatly degrades the overall transmission performance and limits the maximum reach. In this paper, we propose a dual-OSC structure with opposite signals to compensate for performance degradation caused by OSC-induced NPN. This method involves no extra digital signal processing (DSP), which is not only simple but also applicable for universal signal rates. By experimental demonstration, a 1.32-dB gain in Q (dB) for 200G DP-16QAM transmission over 1618-km G.652.D can be done, almost achieving the same performance as the no OSC case.

Помехоустойчивость когерентного приема двоичных сигналов с синусоидальной огибающей в гидроакустическом канале связи

Goals. The main purpose of this work is to develop a methodology for determining the parameters of binary signals, at which the signals become relatively invariant to frequency distortions in the marine environment. The frequency distortion of the signals is caused by the uneven frequency response of the attenuation of the marine environment. The main part of this technique is to assess the effect of frequency distortion of signals on the noise immunity of reception. In accordance with this, the error probabilities of signal receivers with various types of manipulation are determined, which are optimal in the absence of distortion. Methods. The provisions of applied hydroacoustics, the theory of random processes and the theory of transmission of discrete messages are used. The main content. The paper considered a model of a single-beam sonar communication channel, characteristic of the deep sea, when the receiver or transmitter is located in the depths of the sea. The transmission coefficient of the channel is used as a transmission coefficient with a Gaussian amplitude -frequency response and a linear phase-frequency response. The error probabilities of coherent binary signal receivers with amplitude, frequency and phase manipulation with a sinusoidal envelope are determined. Coherent receivers optimal by the criterion of maximum likelihood under the action of white Gaussian noise and the absence of distortion in the marine environment are considered as receivers. A logarithmic measure of increasing the probability of error is introduced, which characterizes the deterioration of noise immunity due to frequency distortions in the channel. For some typical cases, the values of signal parameters that are relatively invariant to frequency distortions in the marine environment are determined. Results. Expressions of the error probability of coherent receivers of binary signals with amplitude, frequency and phase manipulation with a sinusoidal envelope are found. A logarithmic measure of the relative increase in the probability of error compared to the case of no distortion is introduced. The functional dependence of this measure on the duration of sending the signal, the carrier frequency and the initial phase of the signal, as well as on the communication range and the signal-to-noise ratio is determined. On the plane of the carrier frequency, the duration of the signal for each type of signal, the boundary of the region above which the signals are relatively invariant to frequency distortions in the marine environment is constructed, a comparison is made with the case of signals with a rectangular envelope. For communication ranges R = 1.5 km and 3 km and typical carrier frequencies, the minimum values of the duration of invariant signals are given.

Frequency-Agile Coherent Multiple Bands Generation Based on an Asymmetrically-Coupled Optoelectronic Dual-Loop With Recirculating Frequency-Shifting

We propose and demonstrate a frequency-agile coherent multiple bands generator based on an asymmetrically-coupled optoelectronic dual-loop framework with recirculating frequency-shifting. The two loops convert two seed signals into different frequency-shifted signals and respectively replace the original seed signals through feedback modulation, achieving repetitive frequency-shifting in the optical- and the electric-domains. When the two loops are coupled through delivering one continuously frequency-shifted light wave into the other loop to participate in the recirculating frequency-shifting, a carrier-frequency agile multiple bands signal is obtained. By properly controlling the parameters of the seed signals and the two optoelectronic loops, highly reconfigurable and coherent multiple bands can be obtained. A proof-of-concept experiment is carried out. Coherent multiband signals with stepped frequency and hopped frequency covering C- and X-bands are generated. Additionally, using the generated signals, a series of microwave imaging experiments under complex electromagnetic interference (EMI) are demonstrated, showing the advantages of the proposed method in anti-interference and high-resolution imaging.

Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

AbstractThe Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low‐carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber‐optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ∼28‐km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high‐resolution two‐dimensional (2D) S wave velocity (Vs) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high Vs and low Vp/Vs ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.

A thorough experimental investigation on airfoil turbulence interaction noise

This paper on airfoil turbulence interaction noise reveals the nature of the relation between the distortion type of turbulent structures and radiated far-field noise. The turbulence interaction phenomenon is explored through comprehensive simultaneous hot-wire, surface pressure, and far-field noise measurements. Two grid turbulence cases are utilized to examine the effect of the coherent structure's length scale compared to the airfoil's leading-edge radius. The results show that the turbulent structures with a size comparable to the leading-edge radius disperse into smaller three-dimensional structures, losing their spatial coherence in the vicinity of the stagnation point. In contrast, the structures with larger integral length scales distort into highly coherent two-dimensional structures, yielding an increase in the surface pressure fluctuation energy spectra and the chordwise extent of the affected area by the interaction phenomenon, which is found to be responsible for the increased levels of far-field noise. The turbulence characteristics of the flow far upstream of the stagnation point determine the unsteady loading behavior at the stagnation point yet have little influence on the unsteady loading of the full airfoil chord. The stagnation point velocity fluctuations manifest a strong link to the remainder of the airfoil chord, as well as the near-field hydrodynamic to far-field acoustic signal coherence, while demonstrating no communication with the surface pressure fluctuations at the stagnation point.

The Optical Signatures of Stochastic Processes in Many-Body Exciton Scattering.

We review our recent quantum stochastic model for spectroscopic lineshapes in the presence of a coevolving and nonstationary background population of excitations. Starting from a field theory description for interacting bosonic excitons, we derive a reduced model whereby optical excitons are coupled to an incoherent background via scattering as mediated by their screened Coulomb coupling. The Heisenberg equationsof motion for the optical excitons are then driven by an auxiliary stochastic population variable, which we take to be the solution of an Ornstein-Uhlenbeck process. Here, we present an overview of the theoretical techniques we have developed as applied to predicting coherent nonlinear spectroscopic signals. We show how direct (Coulomb) and exchange coupling to the bath give rise to distinct spectral signatures and discuss mathematical limits on inverting spectral signatures to extract the background density of states. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 74 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Characteristic Features of the Antarctic Surface Air Temperature with Different Reanalyses and In Situ Observations and Their Uncertainties

Antarctic surface air temperature (SAT) variability is characterized by strong seasonality and regionality, which are associated with the tropical–polar teleconnections and the radiative forcing caused by the concentration changes in ozone and other greenhouse gases. Nevertheless, the sparse in situ observations and the strong disagreement between different reanalysis datasets hinder coherent conclusions about Antarctic SAT variability. In this study, we use a newly developed statistical method, combined maximum covariance analysis (CMCA), to retrieve coherent SAT modes from six reanalysis datasets and 26 station observations. The results show that the Antarctic SAT variability may be dominated by a continental-wide warming/cooling mode, an East–West Antarctic seesaw mode, and a dipole SAT mode around West Antarctica. These SAT modes are strongly associated with three principal modes of Antarctic atmospheric circulation. Furthermore, all six reanalyses can represent these SAT modes well, compared with the observations, despite a clear deviation over the Antarctic Peninsula associated with the biases in the Foehn wind, which may not be clearly reproduced in a low-resolution reanalysis. This study provides an effective means by which to extract coherent signals from all reanalyses and observations to represent the Antarctic SAT variability, and to improve its predictability and projection.

Local Oscillator Power Adjustment-Based Adaptive Amplification for Coherent TDM-PON With Wide Dynamic Range

Coherent technology is a promising solution for future 100-Gb/s and even 200-Gb/s single-wavelength time-division multiplexing passive optical network (TDM-PON) systems. One of the key issues for coherent TDM-PON is the upstream burst-mode amplification. The limited resolution of the analog-to-digital converter (ADC) makes it challenging to detect burst signals with widely varying power levels. Local oscillator (LO) power adjustment is a promising solution to this problem. In the present study, we verified the feasibility of LO power adjustment for adaptive amplification in a 200-G coherent TDM-PON system. We investigated the overall performance of the system under different implementation conditions, such as ADC sampling scales, TIA MGC mode control voltages, LO optical power levels, and the received optical power (ROP). Simulation and experimental results indicated that LO power adjustment can widen the dynamic range of the coherent PON system. As a proof of concept, we tested the system performance with continuous-mode signals and signals of isolated patterns with a burst-mode data frame. The dynamic range was extended to >30 dB via LO power adjustment, with 38- and 37-dB power budgets for 200-Gb/s/λ coherent TDM-PON continuous signals and signals of isolated patterns, respectively, after a 50-km standard single-mode fiber (SSMF).

Experimental realization of multimode nonlinear parametric amplification from cascading four-wave mixing of dressed atoms.

The nonlinear parametric process is of great significance for achieving high-quality coherent optical signals and quantum correlated photons. With the development of classical and quantum information processing, the study of the properties of parametric processes is evolving in complex scenarios of multimode, which is limited in conventional nonlinear media due to strict phase matching, e.g. nonlinear crystals. Here we study the dressing-energy-level-cascaded four-wave mixing process to generate multimode optical parametric signals. Via cascading double-Λ type configuration of 85Rb D1 line, the non-degenerate energy-level-cascaded FWM is constructed to generate multimode self-parametric amplification. Moreover, with the dressing effects based on atomic coherence, the spatial and frequency multimode characteristics of energy-level-cascaded FWM parametric amplification, i.e., the modes number and pattern, are actively modulated by the pump fields detuning. Also, the spatial modes from the coupling of two coexisting spontaneous parametric FWMs can be controlled to reach tremendous scalability via the atomic coherence and Kerr non-linearity. The atomic coherence effects and unique phase-matching symmetry nature allow flexible modulation of the multimode property of the generated parametric signals within a nonlinear device, which paves a way for multimode classical and quantum information processing.

Multiple spatial and temporal scales of deformation from geodetic monitoring point to active transcrustal magma system at Uturuncu volcano, Bolivia

Abstract Uturuncu volcano in southern Bolivia last erupted around 250 ka but is exhibiting signs of recent activity, including over 50 yr of surface uplift, elevated seismic activity, and fumarolic activity. We studied the spatial and temporal scales of surface deformation from 1992 to 2021 to better understand subsurface activity. We tracked Uturuncu’s recent deformation using interferometric synthetic aperture radar (InSAR) data and the global navigation satellite system (GNSS) station UTUR, located near Uturuncu’s summit. We observed a spatially coherent signal of uplift from 2014 to 2021 from Sentinel-1 A/B satellites that indicates the Altiplano-Puna magma body, located 19–24 km below ground level, and previously noted as the source of the large region of deformation, is still active. The ground is now uplifting at a rate of ~3 mm/yr compared to prior rates of ~10 mm/yr. We corroborated this waning uplift with in situ data from station UTUR. We combined the Sentinel-1 data with TerraSAR-X interferograms to constrain an ~25 km2 region of subsidence located 11 km SSW of Uturuncu, with a source depth of 2.1 km below ground level to an active period of ~2.5 yr with ~5 mm/yr subsidence. We developed a conceptual model that relates these varying depths and time scales of activity in a transcrustal magmatic system. We associate the surface uplift with pressurization from ascending gases and brines from magmatic reservoirs in the midcrust. We infer the existence of brine lenses in the shallow hydrothermal system based on low subsurface resistivity correlated with surface subsidence.

Free-running Yb:KYW dual-comb oscillator in a MOPA architecture.

Single-cavity dual-combs comprise a rapidly emerging technology platform suitable for a wide range of applications like optical ranging, equivalent time sampling, and spectroscopy. However, it remains a challenging task to develop a dual-comb system that exhibits low relative frequency fluctuations to allow for comb line resolved measurements, while simultaneously offering high average power and short pulse durations. Here we combine a passively cooled and compact dual-comb solid-state oscillator with a pair of core-pumped Yb-fiber-based amplifiers in a master-oscillator power-amplifier (MOPA) architecture. The Yb:KYW oscillator operates at 250 MHz and uses polarization multiplexing for dual-comb generation. To the best of our knowledge, this is the first demonstration of a single-cavity dual-comb based on this gain material. As the pulse timing characteristics inherent to the oscillator are preserved in the amplification process, the proposed hybrid approach leverages the benefit of both the ultra-low noise solid-state laser and the advantages inherent to fiber amplifier systems such as straight-forward power scaling. The amplifier is optimized for minimal pulse broadening while still providing significant amplification and spectral broadening. We obtain around 1 W of power per output beam with pulses then compressed down to sub-90 fs using a simple grating compressor, while no pre-chirping or other dispersion management is needed. The full-width half-maximum (FWHM) of the radio-frequency comb teeth is 700 Hz for a measurement duration of 100 ms, which is much less than the typical repetition rate difference, making this passively stable source well-suited for indefinite coherent signal averaging via computational phase tracking.

Highly efficient coherent detection of terahertz pulses based on ethanol

Water-based terahertz (THz) coherent detection scheme has been recently proposed, which overcomes the bandwidth limitation or high probe laser power demand in solid-/gas-based schemes. Here, we report a highly efficient THz coherent detection method using ethanol with superior performances under the mechanism of four-wave mixing. We systematically investigate the energy ratios and relative polarizations between the THz-induced second harmonic and control second harmonic (CSH) beams and reveal that ethanol always exhibits significantly higher detection sensitivity than water. The coherent, incoherent, or hybrid detection mode can be flexibly switched by changing the CSH beam polarization. The enhanced sensitivity derives from the much larger third-order nonlinear coefficient and lower ionization potential of ethanol. In addition, for the ethanol–water mixtures with various concentrations, the THz coherent detection signals can always be decomposed into the linear superposition of those from pure ethanol and neat water at the sub-picosecond timescale, indicating the synergistic contribution of ethanol and water molecules in the mixture during the detection process. This work provides a valid method to significantly improve the sensitivity of the liquid-based coherent detection scheme and a research perspective for exploring the solute–solvent molecular interactions.

Performance Analysis of Scalable Optical Circuit Switch Employing Fast-Tunable AMZI Filters for Coherent Detection

High-port-count optical switches are expected to resolve the envisaged bandwidth and power crunch in intra-data center networks stemming from the slowdown of Moore's Law. This paper briefly reviews electrical switching technologies in current intra-data centers and discusses requirements for optical circuit switches in future data centers. We highlight an optical switch architecture that combines the two independent dimensions of space and wavelength to realize large port counts and fast switching. Wavelength routing is implementable with receiver-side channel selection using wavelength tunable filters (TFs). Coherent detection necessitates a fast-tunable local oscillator (LO) at the receiver. It can be cost-effectively realized using an LO bank that consists of fixed-wavelength laser sources and Silicon-photonic asymmetric Mach-Zehnder interferometer (AMZI) filters. Colorless detection that removes a TF at the front of the receiver is possible when the number of wavelength-division multiplexing (WDM) channels is small, however, as the number exceeds a certain limit the TF is needed to prevent power saturation of the receiver. We present an effective cooperative filtering scheme for transmission signals and LO channels sourced from an LO bank; it can detect C-band WDM coherent signals while easing the receiver's power limitation. The scheme is analyzed to clarify receiver performance and the switch port-count bounds under various operating conditions. We demonstrate that the cooperative filtering scheme effectively works from 60 (typical of coherent receivers) to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ &gt; $</tex-math></inline-formula> 116 wavelength channels, which is verified by experiments for 1,856 × 1,856 optical switching with the short switching time of 3.2 μs.

Small Sample Coherent DOA Estimation Method Based on S2S Neural Network Meta Reinforcement Learning.

Aiming at the existing Direction of Arrival (DOA) methods based on neural network, a large number of samples are required to achieve signal-scene adaptation and accurate angle estimation. In the coherent signal environment, the problems of a larger amount of training sample data are required. In this paper, the DOA of coherent signal is converted into the DOA parameter estimation of the angle interval of incident signal. The accurate estimation of coherent DOA under the condition of small samples based on meta-reinforcement learning (MRL) is realized. The meta-reinforcement learning method in this paper models the process of angle interval estimation of coherent signals as a Markov decision process. In the inner loop layer, the sequence to sequence (S2S) neural network is used to express the angular interval feature sequence of the incident signal DOA. The strategy learning of the existence of angle interval under small samples is realized through making full use of the context relevance of spatial spectral sequence through S2S neural network. Thus, according to the optimal strategy, the output sequence is sequentially determined to give the angle interval of the incident signal. Finally, DOA is obtained through one-dimensional spectral peak search according to the angle interval obtained. The experiment shows that the meta-reinforcement learning algorithm based on S2S neural network can quickly converge to the optimal state by only updating the gradient of S2S neural network parameters with a small sample set when a new signal environment appears.