Fajie Duan

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.

THREE-DIMENSIONAL LOCALIZATION ALGORITHM FOR MIXED NEAR-FIELD AND FAR-FIELD SOURCES BASED ON ESPRIT AND MUSIC METHOD

A three-dimensional (3-D) source localization algorithm of joint elevation, azimuth angles and range estimation for the mixed near-fleld (NF) and far-fleld (FF) sources is presented in this paper. We flrst estimate the elevation angles of all mixed sources by using the generalized ESPRIT method. With the elevation angle estimates, the range parameters of all mixed sources are obtained, and then both the NF and FF sources are distinguished. Finally, with the elevation angle and range estimates, the azimuth angles of all mixed sources are acquired based on the conventional high-resolution MUSIC method. The proposed algorithm avoids parameter match operation, and requires neither a multidimensional search nor high-order statistics (HOS). Simulation and experiment results 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.

Calibration method of the time synchronization error of many data acquisition nodes in the chained system

Time synchronization is very important in a distributed chained seismic acquisition system with a large number of data acquisition nodes (DANs). The time synchronization error has two causes. On the one hand, there is a large accumulated propagation delay when commands propagate from the analysis and control system to multiple distant DANs, which makes it impossible for different DANs to receive the same command synchronously. Unfortunately, the propagation delay of commands (PDCs) varies in different application environments. On the other hand, the phase jitter of both the master clock and the clock recovery phase-locked loop, which is designed to extract the timing signal, may also cause the time synchronization error. In this paper, in order to achieve accurate time synchronization, a novel calibration method is proposed which can align the PDCs of all of the DANs in real time and overcome the time synchronization error caused by the phase jitter. Firstly, we give a quantitative analysis of the time synchronization error caused by both the PDCs and the phase jitter. Secondly, we propose a back and forth model (BFM) and a transmission delay measurement method (TDMM) to overcome these difficulties. Furthermore, the BFM is designed as the hardware configuration to measure the PDCs and calibrate the time synchronization error. The TDMM is used to measure the PDCs accurately. Thirdly, in order to overcome the time synchronization error caused by the phase jitter, a compression and mapping algorithm (CMA) is presented. Finally, based on the proposed BFM, TDMM and CMA, a united calibration algorithm is developed to overcome the time synchronization error caused by both the PDCs and the phase jitter. The simulation experiment results show the effectiveness of the calibration method proposed in this paper.

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 Robust method for constructing rotational invariant descriptors

Abstract Unlike most existing descriptors that only encode the spatial information of one neighborhood for each sampling point, this paper proposed two novel local descriptors which encodes more than one local feature for each sampling point. These two local descriptors are named as MIOP (Multi-neighborhood Intensity Order Pattern) and MIROP (Multi-neighborhood Intensity Relative Order Pattern), respectively. Thanks to the rotation invariant coordinate system, the proposed descriptors can achieve the rotation invariance without reference orientation estimation. In order to evaluate the performance of the proposed descriptors and other tested local descriptors (e.g., SIFT, LIOP, DAISY, HRI-CSLTP, MROGH), image matching experiments were carried out on three datasets which are Oxford dataset, additional image pairs with complex illumination changes, and image sequences with different noises, respectively. To further investigate the discriminative ability of the proposed descriptors, a simple object recognition experiment was conducted on three public datasets. The experimental results show that the proposed local descriptors exhibit better performance and robustness than other evaluated descriptors.

Bio-Inspired Covert Active Sonar Strategy

The covertness of the active sonar is a very important issue and the sonar signal waveform design problem was studied to improve covertness of the system. Many marine mammals produce call pulses for communication and echolocation, and existing interception systems normally classify these biological signals as ocean noise and filter them out. Based on this, a bio-inspired covert active sonar strategy was proposed. The true, rather than man-made sperm whale, call pulses were used to serve as sonar waveforms so as to ensure the camouflage ability of sonar waveforms. A range and velocity measurement combination (RVMC) was designed by using two true sperm whale call pulses which had excellent range resolution (RR) and large Doppler tolerance (DT). The range and velocity estimation methods were developed based on the RVMC. In the sonar receiver, the correlation technology was used to confirm the start and end time of sonar signals and their echoes, and then based on the developed range and velocity estimation method, the range and velocity of the underwater target were obtained. Then, the RVMC was embedded into the true sperm whale call-train to improve the camouflage ability of the sonar signal-train. Finally, experiment results were provided to verify the performance of the proposed method.

A rotationally invariant descriptor based on mixed intensity feature histograms

Abstract This paper proposes a novel method to build a rotation invariant local descriptor by mixed intensity feature histogram. Most existing local descriptors based on intensity ordinal information typically encode only one local feature for each sampling point in the image patch. To address this problem, we proposed a method to encode more than one different local features for each pixel in the image patch and construct a 2D mixed intensity feature histogram, from which our proposed MIFH descriptor is then constructed. Since the rotation invariant coordinate system is adopted, the MIFH descriptor does not need to estimate the reference orientation. In order to evaluate the performance and the robustness of the MIFH with other well-known local descriptors (e.g., SIFT, GLOH, DAISY, HRI-CSLTP, LIOP, MROGH), image matching experiments were carried out on standard Oxford dataset, additional image pairs with complex illumination changes and image sequences with different noises. To further investigate the discriminative ability of the MIFH descriptor, a simple object recognition experiment was conducted on three public datasets. The experimental results demonstrate that our descriptor MIFH exhibits better performance and robustness than other evaluated local descriptors.