scholarly journals An Improved Velocity Estimation Method for Wideband Multi-Highlight Target Echoes in Active Sonar Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2794 ◽  
Author(s):  
Shuxia Huang ◽  
Shiliang Fang ◽  
Ning Han
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Filter Method ◽  
Improved Method ◽  
Matching Algorithm ◽  
Active Sonar ◽  
Estimation Performance ◽  
Effective Performance ◽  
Sonar Systems

In active sonar systems, the target echoes are usually equivalent to a superposition of the Doppler-scaled reflections from multiple highlights. The reflections overlap with each other both in the time and frequency domain, which results in a decreased velocity estimation performance. Recently, the hyperbolic-frequency modulated signal has been widely employed in sonar systems for moving targets due to its Doppler tolerance, while the precise velocity estimation becomes a great challenge under such conditions. In this paper, the echo c is modeled onsidering a target with a constant velocity and multi-highlights. The velocity estimation performance is analyzed though the signal’s matched filter and the wideband ambiguity function. An improved method based on the sliding window matching algorithm is proposed to improve the performance. The method controls the energy of environmental noise and interference by focusing on the dominant target highlight, and applying a designed window which utilizes the Doppler characteristics of hyperbolic-frequency modulated signals. Simulations and lake experiment allow us to compare between the improved method and the conventional matched filter method. The results verify the influence of the multi-highlights in velocity estimation and indicate that the improved method has more effective performance.

scholarly journals Bio-Inspired Covert Active Sonar Strategy

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2436 ◽  
Author(s):  
Jiajia Jiang ◽  
Xianquan Wang ◽  
Fajie Duan ◽  
Chunyue Li ◽  
Xiao Fu ◽  
...  
Keyword(s):  
Marine Mammals ◽  
Estimation Method ◽  
Sperm Whale ◽  
Waveform Design ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Range Resolution ◽  
Active Sonar ◽  
Ocean Noise ◽  
Underwater Target

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.

scholarly journals Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1865
Author(s):  
Gabriel Calassou ◽  
Pierre-Yves Foucher ◽  
Jean-François Léon
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Sequential Method ◽  
Modal Radius ◽  
Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

scholarly journals An Initial Value Estimation Method for the Kalman and Extended Kalman Filters in Underground Metal Detection

2019 ◽  
Vol 9 (19) ◽  
pp. 4113 ◽  
Author(s):  
Yadong Wan ◽  
Zhen Wang ◽  
Peng Wang ◽  
Zhiyang Liu ◽  
Na Li ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Estimation Method ◽  
Detection Methods ◽  
Polarizability Tensor ◽  
Filter Method ◽  
Excellent Performance ◽  
Initial Value ◽  
Initial State ◽  
Metal Detection ◽  
Value Estimation

As an underground metal detection technology, the electromagnetic induction (EMI) method is widely used in many cases. Therefore, the EMI detection algorithms with excellent performance are worth studying. One of the EMI detection methods in the underground metal detection is the filter method, which first obtains the secondary magnetic field data and then uses the Kalman filter (KF) and the extended Kalman filter (EKF) to estimate the parameters of metal targets. However, the traditional KF methods used in the underground metal detection have an unsatisfactory performance of the convergence as the algorithms are given a random or a fixed initial value. Here, an initial state estimation algorithm for the underground metal detection is proposed. The initial state of the target’s horizontal position is estimated by the first order central moments of the secondary field strength map. In addition, the initial state of the target’s depth is estimated by the full width at half maximum (FWHM) method. In addition, the initial state of the magnetic polarizability tensor is estimated by the least squares method. Then, these initial states are used as the initial values for KF and EKF. Finally, the position, posture and polarizability of the target are recursively calculated. A simulation platform for the underground metal detection is built in this paper. The simulation results show that the initial value estimation method proposed for the filtering algorithm has an excellent performance in the underground metal detection.

Weak Signal Detection in Underwater Acoustic Based on Time-Series Characteristic

2011 ◽  
Vol 216 ◽  
pp. 548-552
Author(s):  
Hai Ping Wu ◽  
Shi Jian Zhu ◽  
Jing Jun Lou ◽  
Li Yang Yu
Keyword(s):  
Time Series ◽  
Signal Detection ◽  
Matched Filter ◽  
Doppler Frequency ◽  
High Dimensional ◽  
Filter Method ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Underwater Acoustic ◽  
Radar Echo

For limitation of the matched filter method in underwater acoustic detection,a method of underwater acoustic weak signal detection based on time series characteristic quantity is proposed．Chaotic waveforms, which have thumbtack type ambiguity function, is selected as the waveform of active sonar in the situation of High Dynamic Doppler Frequency Shift. According to the change of correlation dimension while chaotic radar echo appears in the chaotic background, chaotic radar echo is checked out by the means of simulation in the situation of high dimensional chaotic background and low dimensional chaotic background．The method proves out in high dimensional chaotic background．

scholarly journals Fixed Echo Rejection in Sodar Using Noncoherent Matched Filter Detection and Gaussian Mixture Model–Based Postprocessing

2019 ◽  
Vol 36 (1) ◽  
pp. 3-16
Author(s):  
Paul Kendrick ◽  
Sabine von Hünerbein
Keyword(s):  
Radial Velocity ◽  
Matched Filter ◽  
Gaussian Mixture ◽  
Urban Environments ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Chirp Pulse ◽  
Signal Processing Algorithm ◽  
Doppler Sodar ◽  
Wind Profiles

AbstractDoppler sodar is a technology used for acoustic-based remote sensing of the lower planetary boundary layer. Sodars are often used to measure wind profiles; however, they suffer from problems caused by noise (both acoustic and electrical) and echoes from fixed objects, which can bias radial velocity estimates. An experimental bistatic sodar was developed with 64 independent channels. The device enables flexible beamforming; beams can be tilted at the same angle irrelevant of frequency, a limitation in most commercial devices. This paper presents an alternative sodar signal-processing algorithm for wind profiling using a multifrequency stepped-chirp pulse. A noncoherent matched filter was used to analyze returned signals. The noncoherent matched filter combines radial velocity estimates from multiple frequencies into a single optimization. To identify and separate sources of backscatter, noise, and fixed echoes, a stochastic pattern-recognition technique, Gaussian mixture modeling, was used to postprocess the noncoherent matched filter data. This method allowed the identification and separation of different stochastic processes. After identification, noise and fixed echo components were removed and a clean wind profile was produced. This technique was compared with traditional spectrum-based radial velocity estimation methods, and an improvement in the rejection of fixed echo components was demonstrated; this is one of the major limitations of sodar performance when located in complex terrain and urban environments.

Impact of strong direct blast on active sonar systems

2015 ◽  
Vol 51 (2) ◽  
pp. 894-909 ◽  
Author(s):  
Luzhou Xu ◽  
Jian Li ◽  
Akshay Jain
Keyword(s):  
Active Sonar ◽  
Sonar Systems
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