Direction-of-arrival estimation

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Direction-of-Arrival Estimation through Exact Continuous l20-Norm Relaxation

Direction-of-Arrival Estimation through Exact Continuous l20-Norm Relaxation

2 kAZ − Yk 2 F + λkZk 2,0 , (5) where λ > 0 balances between data-fidelity and sparsity. This problem is nonconvex, noncontinuous, and NP hard due to its combinatorial nature. Yet, the single measurement vector (SMV) case (i.e., L = 1) has been widely studied, driven by the compressed sensing paradigm. Naturally, many of these approaches have been extended to the MMV setting, such as those mentioned in the introduction. Such extensions are essential as the resolution of MMV problems leads to an improvement in the size of the recoverable support [25].

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3D direction-of-arrival estimation using a wideband vector antenna

3D direction-of-arrival estimation using a wideband vector antenna

‡ Toulouse University, F-31400 Toulouse, France § DGA, F-75509 Paris, France Abstract—In this communication, direction finding perfor- mances of a reconfigurable wideband vector antenna are pre- dicted. The accurate estimation of the direction of arrivals across the 3D half-space of incoming electromagnetic fields is obtained over a 1.7:1 frequency range from only two colocated and orthogonal circular arrays of Vivaldi antennas.

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Direction of Arrival Estimation with Coprime Arrays

Direction of Arrival Estimation with Coprime Arrays

Direction of arrival (DOA), defined by the incident angles of incoming signals, is one of the most significant array signal parameters, and DOA estimation has been considered as a crucial issue in radar, sonar and other systems where sensor arrays are involved. In the last decades, DOA estimation has been well studied based on uniform linear arrays (ULAs), of which the sensor elements are uniformly distributed in a straight line with inter-element spacing equaling to a half-wavelength of incoming signals to avoid ambiguities. Many algorithms have been proposed for DOA estimation, including beamforming based methods like classical beamforming method and Capon method, and high resolution subspace based methods like MUSIC and ESPRIT. However, for ULA configuration, the array aperture is limited by its small inter-element spacing, resulting in unsatisfying estimation performance. On the other hand, only up to M − 1 sources can be detected with M sensor elements, therefore numerous sensor elements will be required when the number of incoming signals is large, which is unrealistic and hard to be accomplished in terms of practical applications. Recently, sparse array configurations have attracted lots of attention. Being superior to traditional ULAs, sparse arrays, with sparsely located sensor elements, can achieve a larger array aperture with fewer sensors, improving estimation performance. Besides, by exploiting the difference coarray obtained from the observation of the physical sensor array, a long virtual half-wavelength spacing ULA can be obtained. With more distinct lags than the number of physical sensor elements, the virtual ULA can be used to perform the DOA estimation, and much more sources can be detected.
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A Method for 3D Direction of Arrival Estimation for General Arrays Using Multiple Frequencies

A Method for 3D Direction of Arrival Estimation for General Arrays Using Multiple Frequencies

SW med (black dots), individual wavelengths SW (grey circles). Non-square array and irregularly spaced sensors. We illustrate the performance of the proposed method for sensor arrangements on non-square domains and with unequal spac- ing (using 129 sensors). The domains considered are depicted in Fig. 2 (left) for equidistant (top) and and irregular (bottom) spacing, respectively. Results obtained for 100 independent noise realizations and SNR values of −10dB and −5dB are plotted in Fig. 2 (center and right column, respectively; same color code as in Fig. 1). Comparison with Fig. 1 yields the following conclusions. First and foremost, the proposed method is clearly effective for general sensor arrangements on non-square domains as well as for the case of irregularly spaced sensors, with performance comparable to those for the square regularly spaced sensor array. Second, the proposed joint wavelength based procedure DOA joint dramatically out-
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Direction of arrival estimation by a modified orthogonal propagator method with spline interpolation

Direction of arrival estimation by a modified orthogonal propagator method with spline interpolation

Researchers attempt to reduce the noise impact by estimat- ing the power of the noise [8], [9], [10] or applying signal enhancement techniques [11], [12]. Stoica et al. propose an eigenvalue-based method [8] to estimate the noise power, which requires the EVD on the data covariance matrix. The noise power is estimated by calculating the average of the eigenvalues belonging to the noise subspace. The eigenvalue method is proven to be statistically efficient [8]. However, it is not the focus of this paper since the major merit of the propagator-based methods is to avoid any EVD or SVD operation. In addition, Stoica et al. [8], Marcos and Sanchez- Araujo [6] also propose two different linear methods. In their methods, the noise power can be extracted from the structure of the data covariance matrix without EVD or SVD operation. These two linear methods are more computationally efficient, yet less statistically efficient, compared with the eigenvalue based methods [8].
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Approximate Unconditional Maximum Likelihood Direction of Arrival Estimation for Two Closely Spaced Targets

Approximate Unconditional Maximum Likelihood Direction of Arrival Estimation for Two Closely Spaced Targets

V. C ONCLUSIONS This paper proposed to exploit a little known asymptotic formulation of the UML criterion together with an asymptotic approximation for small separation between two frequencies. As a result, a 1D-minimization procedure only is needed to estimate the two frequencies, which yields a computationally simple algorithm. The latter exhibits near efficient perfor- mance up to half the main lobe width frequency difference and an even better resolution than UML in case of very close sources. Moreover, we also get equivalent UML performance in case of highly correlated or coherent sources where the proposed method outperforms the CML algorithm as well as common high resolution techniques.
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A Method for 3D Direction of Arrival Estimation for General Arrays Using Multiple Frequencies

A Method for 3D Direction of Arrival Estimation for General Arrays Using Multiple Frequencies

SW med (black dots), individual wavelengths SW (grey circles). Non-square array and irregularly spaced sensors. We illustrate the performance of the proposed method for sensor arrangements on non-square domains and with unequal spac- ing (using 129 sensors). The domains considered are depicted in Fig. 2 (left) for equidistant (top) and and irregular (bottom) spacing, respectively. Results obtained for 100 independent noise realizations and SNR values of −10dB and −5dB are plotted in Fig. 2 (center and right column, respectively; same color code as in Fig. 1). Comparison with Fig. 1 yields the following conclusions. First and foremost, the proposed method is clearly effective for general sensor arrangements on non-square domains as well as for the case of irregularly spaced sensors, with performance comparable to those for the square regularly spaced sensor array. Second, the proposed joint wavelength based procedure DOA joint dramatically out-
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Direction of arrival estimation in a mixture of K-distributed and Gaussian noise

Direction of arrival estimation in a mixture of K-distributed and Gaussian noise

a b s t r a c t We address the problem of estimating the directions-of-arrival (DoAs) of multiple signals received in the presence of a combination of a strong compound-Gaussian external noise and weak internal white Gaussian noise. Since the exact distribution of the mixture is not known, we get an insight into optimum procedure via a related model where we consider the texture of the compound-Gaussian component as an unknown and deterministic quantity to be estimated together with DoAs or a basis of the signal subspace. Alternate maximization of the likelihood function is conducted and it is shown that it operates a separation between the snapshots with small/large texture values with respect to the additive noise power. The modified Cramér–Rao bound is derived and a prediction of the actual mean-square error is presented, based on separation between external/internal-noise dominated samples. Numerical simu- lations indicate that the suggested iterative DoA estimation technique comes close to the introduced bound and outperform a number of existing routines.
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Direction of arrival estimation by modified orthogonal propagator method with linear prediction in low SNR scenarios

Direction of arrival estimation by modified orthogonal propagator method with linear prediction in low SNR scenarios

Email:(jingjing.pan1@etu.univ-nantes.fr) Abstract In propagator based methods for Direction of Arrival (DoA) finding, conventional approaches for eliminating the noise impact are based on signal enhancement or noise power estimation. In this paper, a new method is introduced from another point of view. When the noise is an additive spatially and temporally white Gaus- sian noise, theoretically, it only impacts the diagonal elements of the data covariance matrix. Firstly, the proposed method utilizes the principle of Linear Prediction (LP) to rebuild the denoised diagonal elements of the data covariance matrix. Then, the Orthogonal Propagator Method (OPM) is directly applied for DoA estimation. Compared with the conventional OPM-based methods, the proposed method is more robust to the noise, especially in low Signal to Noise Ratio (SNR) scenarios. Simula- tion examples are provided to demonstrate the performance of the proposed method. Keywords: Direction of Arrival (DoA) estimation, Linear Prediction (LP),
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An enhanced spatial smoothing technique with ESPRIT algorithm for direction of arrival estimation in coherent scenarios

An enhanced spatial smoothing technique with ESPRIT algorithm for direction of arrival estimation in coherent scenarios

Jingjing Pan, Meng Sun, Yide Wang, Xiaofei Zhang Abstract—Subspace-based methods suffer from the rank loss of the noise free data covariance matrix in the context of direction of arrival (DOA) estimation of coherent sources. The well-known spatial smoothing techniques are then widely employed to create a rank restored data covariance matrix. However, conventional spatial smoothing techniques, such as the spatial smoothing pre-processing (SSP), modified spatial smoothing pre-processing (MSSP), and improved spatial smoothing (ISS), do not make full use of the available information in the data covariance matrix. In this paper, an enhanced spatial smoothing (ESS) technique is proposed to exploit both the covariance matrices of indi- vidual subarrays and the cross-covariance matrices of different subarrays. Besides, the proposed method can work directly on the signal subspace (ESS-SS), since the signal subspace contains all the information of the DOAs of incoming signals. After de- correlation, the subspace method ESPRIT is adopted to estimate the DOAs. Compared with conventional approaches, the proposed method is more powerful to de-correlate the correlation between signals, and also more robust to the noise impact. The proposed method is tested on numerical data in coherent scenarios, and compared with conventional approaches. Simulation results show that the proposed method has an enhanced resolving capability and a lower signal-to-noise ratio threshold.
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On an Iterative Method for Direction of Arrival Estimation using Multiple Frequencies

On an Iterative Method for Direction of Arrival Estimation using Multiple Frequencies

V. C ONCLUSIONS We have proposed a novel high-resolution method for direction of arrival estimation based on multiple frequency or wideband measurements. The method makes use of the Kronecker theorem for implicitly imposing the model equa- tions for each considered frequency through rank penalization of the Hankel matrices generated by the corresponding ap- proximating sequences. The resulting optimization problem is then resolved using ADMM. Although the problem is non- convex (and hence inherits the problem of local minima), numerical simulations demonstrate that the method yields excellent practical performance. In particular, it significantly outperforms ESPRIT based estimation, both at low and high SNR levels, and enables to obtain practically usable estimates even at very low SNR. Furthermore, the proposed method yields an algorithm that is simple and easy to implement.
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On an Iterative Method for Direction of Arrival Estimation using Multiple Frequencies

On an Iterative Method for Direction of Arrival Estimation using Multiple Frequencies

V. C ONCLUSIONS We have proposed a novel high-resolution method for direction of arrival estimation based on multiple frequency or wideband measurements. The method makes use of the Kronecker theorem for implicitly imposing the model equa- tions for each considered frequency through rank penalization of the Hankel matrices generated by the corresponding ap- proximating sequences. The resulting optimization problem is then resolved using ADMM. Although the problem is non- convex (and hence inherits the problem of local minima), numerical simulations demonstrate that the method yields excellent practical performance. In particular, it significantly outperforms ESPRIT based estimation, both at low and high SNR levels, and enables to obtain practically usable estimates even at very low SNR. Furthermore, the proposed method yields an algorithm that is simple and easy to implement.
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Direction of Arrival Estimation in Low-Cost Frequency Scanning Array Antenna Systems

Direction of Arrival Estimation in Low-Cost Frequency Scanning Array Antenna Systems

Performance of two DOA estimation algorithms, MVB and ML estimation are studied. These methods were first adapted for our signal model and their performance were investigated through Monte Carlo simulations and compared against each other in terms of root mean square error. Simulation results showed that in low SNR situations, the RMSE of DOA estimation is large and the MVB method cannot separate two targets. In addition, it was shown that sampling from sidelobes of the antenna pattern decreases the performance of the MVB method. In other cases, by selecting correct parameters, both methods can separate targets with angular separations smaller than the antenna pattern beamwidth. We have also presented a calibration scheme which worked efficiently when it was applied to different antenna pattern shapes at each frequency and nonuniform scanning angles. In the next step, the proposed methods will be applied to the experimental data captured from a radar experiment using real targets.
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Approximate maximum likelihood direction of arrival estimation for two closely spaced sources

Approximate maximum likelihood direction of arrival estimation for two closely spaced sources

eric.chaumette@onera.fr Abstract—Most high resolution direction of arrival (DoA) estimation algorithms exploit an eigen decomposition of the sample covariance matrix (SCM). However, their performance dramatically degrade in case of correlated sources or low number of snapshots. In contrast, the maximum likelihood (ML) DoA estimator is more robust to these drawbacks but suffers from a too expensive computational cost which can prevent its use in practice. In this paper, we propose an asymptotic simplification of the ML criterion in the case of two closely spaced sources. This approximated ML estimator can be implemented using only 1-D Fourier transforms. We show that this solution is as accurate as the exact ML one and outperforms all high-resolution techniques in case of correlated sources. This solution can also be used in the single snapshot case where very few algorithms are known to be effective.
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Celebration of arrival and departure : airport as threshold between sky and ground

Celebration of arrival and departure : airport as threshold between sky and ground

Unfortunately, travelers do not notice Sakurajima from the existing old Kagoshima Airport Terminal because of the uniform circulation which has no relation with its own site c[r]

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Performances Analysis of a System of Localization by Angle of Arrival UWB Radio

Performances Analysis of a System of Localization by Angle of Arrival UWB Radio

The increasingly widespread use of sensor and actuator networks and in gen- eral of the Internet of Things (IoT) in several areas of precision, imposes upon localization systems that can often equip them with a robust and more precise localization. It is in this sense that UWB technology has proved to be one of the most powerful communication technologies for these localization systems; thanks, in particular to the bandwidth occupied instantaneously by the signal allowing a very fine temporal resolution. Constructors have set up localization kits based on various technologies. These kits facilitate in a way the work of localization of users. In this paper, we present results on the per- formance study of the Decawave PDoA Kit. This Kit uses the PDoA (Phase Difference of Arrival) to determine the Angle of Arrival (AoA) parameter with UWB technology. This study is in context of localization by AoA for an application to protect agricultural crops against grain-eating birds. The re- sults of the study show overall AoA measurement errors around 10 degrees in an ideal environment.
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Performances Analysis of a System of Localization by Angle of Arrival UWB Radio

Performances Analysis of a System of Localization by Angle of Arrival UWB Radio

The increasingly widespread use of sensor and actuator networks and in gen- eral of the Internet of Things (IoT) in several areas of precision, imposes upon localization systems that can often equip them with a robust and more precise localization. It is in this sense that UWB technology has proved to be one of the most powerful communication technologies for these localization systems; thanks, in particular to the bandwidth occupied instantaneously by the signal allowing a very fine temporal resolution. Constructors have set up localization kits based on various technologies. These kits facilitate in a way the work of localization of users. In this paper, we present results on the per- formance study of the Decawave PDoA Kit. This Kit uses the PDoA (Phase Difference of Arrival) to determine the Angle of Arrival (AoA) parameter with UWB technology. This study is in context of localization by AoA for an application to protect agricultural crops against grain-eating birds. The re- sults of the study show overall AoA measurement errors around 10 degrees in an ideal environment.
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Impact of Iris Size and Eyelids Coupling on the Estimation of the Gaze Direction of a Robotic Talking Head by Human Viewers

Impact of Iris Size and Eyelids Coupling on the Estimation of the Gaze Direction of a Robotic Talking Head by Human Viewers

mainly related to the distance between agent's eyes and target tiles, whatever the conditions and independently of adjustment of the eyelid positions: largest errors were made to report the estimated tiles on a Distance separating the human eyes and the ground was set to 115 cm. To control the possible impact of the head orientation on gaze reading, the experimenter Figure 6). The tiles chosen randomly by the system were communicated to the experimenter by earphones. Just as in the HRI setup, the tone and the trial's number were heard by the participant who has Participants were informed about the random order of the conditions (i.e., they will perform the task four times with all of our three different robot's caps and with eyes' experimenter in random order) and the fact that the targeted tiles are randomly chosen (i.e., 64 tiles among the 100 are randomly chosen by the program). They were not informed that peripheral tiles are never looked at. In addition, they position adjustments that were again randomly activated. Lightings in the room were control their possible impact on gaze
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Arrival Time Statistics in Global Disease Spread

Arrival Time Statistics in Global Disease Spread

network. We have simulated, using the model developed in [1], and summarized above, a spreading phenomenon on a subnetwork of the WAN, composed of the 2, 400 nodes for which the populations are larger than 10, 000 inhabitants and which corresponds to 98% of the total traffic [24]. The arrival times are computed by solving numerically the equations of the Rvachev-Longini model with dis- cretized random travel events, and averaging over 1, 000 realizations of the spreading with the same seed (one infectious individual in a given city). Figure 4 shows the obtained values of λhti versus χ for various initial seeds. We observe that the average arrival time is indeed determined by the value of χ in a given city: various cities with the same χ are reached at the same time by the disease propagation. While χ quantitatively overesti- mates the arrival time, the two quantities are correlated strongly enough, in order to obtain with a good confi- dence the order of arrival of the disease in different cities. More precisely, if we denote ∆χ(i, j) =| χ(j) − χ(i) |, we show in Fig. 5 the probability f c (∆χ) that the ar-
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Optimization of Arrival and Departure Routes in Terminal Maneuvering Area

Optimization of Arrival and Departure Routes in Terminal Maneuvering Area

Abstract—Airport is both the starting and ending point of air traffic. The sharp increase in air traffic flow causes directly traffic congestion in Terminal Maneuvering Area (TMA) which affects the normal operation of the flights. Optimizing departure and arrival procedures is therefore crucial to regulate air traffic flow. This research focuses on generating 3D Standard Instrument Departure routes and Standard Terminal Arrival Routes in TMA at a strategic level. We propose an optimization approach to generate 3D routes avoiding obstacles and assuring a minimum separation between routes. The method combines Fast Marching Method and Simulated Annealing.
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