Target tracking based on frequency spectrum amplitude

The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The prohabilisfic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking.

Amplitude and Phase Analysis Based on Signed Demodulation for AM-FM Signal

This paper proposes a new amplitude and phase demodulation scheme different from the traditional method for AM-FM signals. The traditional amplitude demodulation assumes that the amplitude should be non-negative, and the phase is obtained under the case of non-negative amplitude, which approximates the true amplitude and phase but distorts the true amplitude and phase in some cases. In this paper we assume that the amplitude is signed (zero, positive or negative), and the phase is obtained under the case of signed amplitude by optimization, as is called signed demodulation. The main merit of the signed demodulation lies in the revelation of senseful physi- cal meaning on phase and frequency. Experiments on the real-world data show the efficiency of the method.

Analysis on Spiral Search Pattern for Moving Target

The distribution function of the target moving in constant velocity and linear course and its meeting condition to the searcher are analyzed.Another proof method for spiral search pattern is presented and the mathematic model of the target possible position is established when performing the linear search.Base on them,the wrong idea about the spiral search pattern can be

Effect of Seabed Topography Change on Sound Ray Propagation—A Simulation Study

Variation of ocean environmental parameters is important to sound ray propagation. This article studies the problem of sound ray propagation in seawater by BELLHOP ray model. The sensitivities of sound ray propagation to the variations of seabed topography and depth of sound source by simulation. The results show that the depth variation of sound source is the main cause for emerging and disappearing of surface sound channel, accumulation area and deep sound channel. The deviation of sound ray propagation is in accordance with seabed topography change.

The Properties and Fast Algorithm of Quaternion Linear Canonical Transform

The quaternion linear canonical transform (QLCT) is defined in this paper, with proofs given for its reversibility property, its linear property, its odd-even invariant property and additivity property. Meanwhile, the quaternion convolution (QCV), quaternion correlation (QCR) and product theorem of LCT are deduced. Their physical interpretation is given as classical convolution, correlation and product theorem. Moreover, the fast algorithm of QLCT (FQLCT) is obtained, whose calculation complexity for different signals is similar to FFT. In addition, the paper presents the relationship between the convolution and correlation in LCT domains, and the convolution and correlation can be calculated via product theorem in Fourier transform domain using FFT.

Direction of arrival estimation and signal recovery based on single snapshot compressed sensing in frequency domain

Direction of arrival （DOA） estimation and signal recovery is the base of the under- water target localization, tracking and recognition. Based on the compressed sensing theory, a method for DOA estimation and source signal recovery is proposed using the single snap- shot processing of the received array signal in frequency domain. The received array signal are transformed to frequency domain, and the single snapshot data in frequency domain are re- garded as the measured data of the compressed sensing. According to the frequency, searching orientation and array manifold, the overcomplete array manifold is constructed as the sensing matrix of the compressed sensing. Both the target signal and power of the searching orientation are estimated by the basis pursuit method to complete DOA estimation and signal recovery. Simulation results show that the proposed method has a number of advantages over the mini- mum variance distortionless response （MVDR） method, including improved robustness to noise, fewer requirement in number of sensors and snapshots. And the correlation coefficient of the signal reaches up to 0.89. Experiment results in real environments verify that the proposed method performs more effectively in the detection of weak targets than the MVDR method and can be applied to real sonar system.

Direction of arrival estimation for underwater acoustic target based on compressed sensing after blind reconstruction of array signal in frequency domain

The performance of direction of arrival(DOA)estimation based on compressed sensing(CS)decreases in the complex ocean marine environment.In order to tackle this problem,a method of DOA estimation for underwater acoustic target based on CS after blind reconstruction of array signal in frequency domain is proposed.Firstly,the received array data are transformed to frequency domain by Fourier transform and frequency domain wideband signal are divided into part overlapping multiple sub-band array signal.Secondly,each subband array signal are separated using plural blind source separation(BSS)method,the sub-band separated matrix and target signal can be estimated.Thirdly,the array signal in frequency domain are reconstructed according to the separated matrix and separated signals which were not noises.Fourthly,the sub-band spatial spectrum corresponding to the reconstructed array signal is obtained by CS beamforming method.Finally,the total spatial spectrum is achieved by summing the all sub-band spatial spectrum.And the target direction can be estimated by searching the peak value of the total spatial spectrum.The verification results of simulator data and sea measured data show that,under the same conditions,the target detection ability and direction precision of the proposed method is superior to the classical minimum variance distortionless response(MVDR)method,frequency domain CS method,BSS combined with MVDR method.The spatial spectrum energy of faint target signal is improved obviously,and the ability of the sonar to detect faint target is enhanced.

Tensor feature extraction of underwater passive sonar target based on auditory model

Feature extraction is a key step for underwater passive sonar target classification and recognition.A kind of tensor feature extraction method based on auditory PattersonHoldsworth cochlear model is proposed.First,the filter impulse response of the cochlear model is regarded as the basis function of signal decomposition,and the center frequency of different channels is determined according to the nonlinear scale or conventional linear scale of the auditory model.Then,the gain and bandwidth of the corresponding channel are calculated,and the order and phase parameters of the impulse response are quantified to obtain a relatively complete signal decomposition basis.And according to the principle of signal decomposition,the third-order tensor features of channel number-order number-phase number are obtained.Finally,the classification and recognition of the underwater passive sonar target is realized by calculating the similarity between the testing sample tensor feature and training sample tensor feature.The experiment on passive sonar target classification and recognition shows that the extracted tensor features have better classification and recognition performance,and the equivalent rectangular bandwidth scale of the auditory model is better than the linear scale to divide the center frequency,which can improve the target indication ability of passive sonar.