Xiangning Hua

Mixed Near-Field and Far-Field Sources Localization Using the Uniform Linear Sensor Array

Based on the ESPRIT-like and polynomial rooting methods, a high-performance and low computational cost localization algorithm for the mixed near-field sources (NFS) and far-field sources (FFS) is proposed using the uniform linear sensor array. First, we combine the steering vectors of the two subarrays to eliminate the range parameters and then yield a new steering vector, which only contains direction-of-arrival (DOA) information. Second, based on the ESPRIT-like and polynomial rooting methods, the DOAs of all NFSs and FFSs are obtained from the new steering vector. Third, with the DOA estimates, the range parameters are estimated depending on the polynomial rooting method again; and further according to the number of the closest to the unit circle roots, we can determine the number of sources at the same DOA direction. Finally, based on the size of the range parameters, the types (NFS or FFS) of sources can be confirmed. In addition, the proposed algorithm does not require the high-order statistics or any 1- or 2-D search and thus has low computational cost. Meanwhile, it makes full use of the array aperture and obtains outstanding estimation performance for both the DOA and range parameters. Moreover, the proposed algorithm avoids parameter match procedure. Numerical experiments show the performance of the proposed algorithm in this paper.

Two New Estimation Algorithms for Sensor Gain and Phase Errors Based on Different Data Models

Gain and phase errors sensitivity is an issue common to all high-resolution direction-of-arrival estimators. In this paper, we first provide the conventional and improved data models. Second, based on the conventional data model, an algorithm called estimation algorithm for the conventional data model (EACDM) is proposed to estimate the gain and phase errors existing in the sensor array for the uniform linear array (ULA). Finally, based on the improved data model, another algorithm called estimation algorithm for the improved data model (EAIDM) is proposed to estimate the gain and phase errors for the ULA. Derivation of these two proposed algorithms (EACDM and EAIDM) is similar. Moreover, the two proposed algorithms perform independently of phase errors, namely, the estimation accuracy is not affected regardless of how large the phase errors are. Furthermore, the computational complexity of the two proposed algorithms is lower than the conventional estimation method. Computer simulations are shown to verify the efficacy of the two proposed algorithms.

Synchronization sampling method based on delta-sigma analog-digital converter for underwater towed array system

Synchronization sampling is very important in underwater towed array system where every acquisition node (AN) samples analog signals by its own analog-digital converter (ADC). In this paper, a simple and effective synchronization sampling method is proposed to ensure synchronized operation among different ANs of the underwater towed array system. We first present a master-slave synchronization sampling model, and then design a high accuracy phase-locked loop to synchronize all delta-sigma ADCs to a reference clock. However, when the master-slave synchronization sampling model is used, both the time-delay (TD) of messages traveling along the wired transmission medium and the jitter of the clocks will bring out synchronization sampling error (SSE). Therefore, a simple method is proposed to estimate and compensate the TD of the messages transmission, and then another effective method is presented to overcome the SSE caused by the jitter of the clocks. An experimental system with three ANs is set up, and the related experimental results verify the validity of the synchronization sampling method proposed in this paper.

Two-dimensional Angles Estimation Method and Its Improved Methods for Single Source with a Sparse Array

Based on two orthogonal linear sparse arrays (LSA) which consist of the coupled-sensors (CSs), a high resolution and no ambiguity (HRNA) method is proposed to estimate the two-dimensional (2D) angles of single source. The HRNA method flrst constructs a new covariance matrix to achieve no ambiguity independent angles estimation by using the covariance matrix generated by each LSA, and then computes joint elevation and azimuth angles by utilizing both the estimated independent angles and triangular relationship. For large array aperture of the LSA, the HRNA method earns a high angle resolution; however, its independent angles estimation accuracy is slightly lower than the multiple signal classiflcation (MUSIC) with a uniform linear array (ULA). In order to enhance the independent angle estimation performance, flrst improved HRNA (FI-HRNA) method is developed based on the HRNA and MUSIC methods. Further, in order to decrease the computational cost, second improved HRNA (SI-HRNA) method is presented based on FI-HRNA and MUSIC methods. The proposed SI-HRNA method obtains high angle resolution, high angle estimation accuracy and low computational load. In addition, the spacing between two adjacent CSs is not limited, and thus the angle resolution and estimation accuracy can be set according to practical demand. Numerical experiment and comparison with the other existing algorithms verify the efiectiveness and superior performance of the method proposed in this paper.

Offshore towed hydrophone linear array: principle, application, and data acquisition results

An underwater acoustic sensing array was presented in this article. With the high-precision sampling clock generation and transmission system, the array can acquire signals synchronously in sub-microsecond level, which is important in offshore environment. Meanwhile, real-time data transmission and storage system was established. All of the data received in host computer can be saved and displayed immediately. Data acquisition experiment was implemented in freshwater reservoir near Tianjin city,China, and the results of the signal wave show that the acquisition and transmission system of hydrophone array can be used to get the underwater information by acoustic exploration.

A NEW measurement and calibration method of the synchronization sampling error of sensor array

All seismic signal acquisition nodes must be synchronized so that they have the same sampling time for seismic signal acquisition in a distributed chained system with a large number of acquisition nodes. However, the propagation delay generated by the long-distance transmission link causes a synchronization acquisition error. In order to correct accurately the synchronization acquisition error, getting the accurate propagation delay size is a necessary condition. With regards to these, based on the detailed analysis of the propagation delay, a model and method for accurately measuring the propagation delay are proposed. Based on the model and method, the propagation delay can be measured accurately and then the delay calibration size can be transmitted to the corresponding acquisition node only through one transmission line. Then, an easy calibration method is proposed, and through it, the synchronization error can be completely eliminated. Simulation results show the effectiveness of the model and method proposed in the paper.

LOCALIZATION OF 3D NEAR-FIELD SOURCE USING THE APERTURE EXTENSION METHOD AND NONUNIFORM CROSS ARRAY

Depending on the aperture extension (AE), a high performance three-dimensional (3D) near-fleld (NF) source localization algorithm is proposed with the nonuniform linear array (NLA). The proposed algorithm flrst generates some flctitious sensors to extend the array aperture by constructing a new Toeplitz matrix, and then obtains a two-dimensional (2D) covariance matrix which only contains the elevation angle and range parameters, and another 3D covariance matrix which contains the elevation/azimuth angle and range parameters. Then based on the 2D covariance matrix, both the elevation angle and range parameters are estimated by using the NLA along the Z axis. With the estimates of both the elevation angle and range parameters and combining the 3D covariance matrix, the estimates of the azimuth angle parameters are obtained using the NLA along the Y axis. The proposed algorithm has four main merits: i) unlike some classical NF source localization algorithms, the quarter-wavelength sensor spacing constraint is not required and more sources can be located simultaneously by the proposed algorithm; ii) the 3D parameters of the proposed algorithm are paired automatically; iii) the 3D search required in conventional 3D multiple signal classiflcation (MUSIC) algorithm is replaced with only one-dimensional (1D) search, and thus the computational burden is reduced; iv) the proposed algorithm gains superior parameter estimation accuracy and resolution.