Mode Domain Signal Processing Technique And Its Application In Underwater Acoustic System

The air targets such as helicopters are dominant in the aeronaval antagonism system because of its efficient hunting performance and agile maneuverability, which is a great threat to the existence of submarines.The subjects investigated in this dissertation are some pivotal passive detecting techniques related to the aeronaval antagonism system aimed to do some helpful research in the development and realization of aeronaval-antagonism SONAR system.Hilbert-Huang Transform (HHT) is a kind of nonlinear signal processing theory. Simulation results have approved that empirical mode decomposition (EMD) can emphasize the local instantaneous characters of original signals and decomposes the multi-component signals into mono-component signals. Aiming at different actual applications, the selection principles of intrinsic mode functions (IMF) are proposed, which could be used in denoising, cross-correlation peak detection and multiple-target recognition. The common single vector sensor azimuth estimation theories are reviewed such as acoustic intensity averager, cross-spectrum method, energy weighted histogram and analytic acoustic intensity method. Extending to array signal processing, the output and natural directivity of the uniform line array are introduced. Meanwhile, the array gain and vector advantage were emphasized.The noise spectrum radiated from air targets consists of line and continuous spectrum, in which the line spectrum noises are principal noise sources.In order to extract line and continuous spectrum, a new algorithm based on EMD was proposed. Some sound energy is transmitted into water when sound goes by the air-water interface, so its underwater field also holds obvious line spectrum characteristic. In low-frequency stage, there is phase different between p and v, so the sound energy leaks out between active and reactive component of acoustic intensity flux, which made conventional azimuth estimation theories biased. Based on lake and sea experiment, this dissertation probes into azimuth estimation methods of air targets using the information of underwater field, and a scheme including detection and identification of air targets has been proposed in which considered the waveband of line spectrum, the ratio of Doppler frequency offset to original frequency and the azimuth (movement changing tendency) of line frequency as the characteristic of air targets.Meanwhile the approximate azimuth information is advantaged for underwater platform to dodge and attack air targets effectually, which is helpful to improve submarines inferior position.The transient signals such as splashes sound of target's water entry and underwater target-starting sound are very important for targets'detection. The character of targets'water entry splash sound and its waveform are studied in this dissertation which can provide a theoretical basis for the identification of water-entry sound and the forecast of impact sound's source level.Combining the character of EMD and the advantage of acoustic intensity averager in single target azimuth estimation, mode acoustic intensity averager (MAIA) method is proposed in this dissertation. By MAIA algorithm, water-entry sound and underwater target-starting sound could be detected and their azimuth could be estimated in the strong interferences flat-form, which was helpful for transient signals detection.The vector array MVDR beam forming algorithm can estimate the omni-directional spatial spectrum effectively, but it's difficult to detect weak targets. Combining the IMF's narrow-band character and its advantage of weak signal detection, the vector array mode domain MVDR algorithm is proposed in this dissertation, in which the decomposed IMFs of the same order from pressure and particle velocity are used to estimate their spatial spectrum.Meanwhile applying the central frequency conception in each IMF, the central frequencies of different order are obtained by the IMF of pressure and particle velocity, and the IMF's central frequencies are considered as the central frequency of MMVDR algorithm. The sea trial results show MMVDR algorithm can enhance the weak signal's spatial spectrum energy effectively meanwhile keep the interference spectrum energy unchanged, and can detect the weak target effectively in strong interference, which can increase the detection distance of weak targets. The steered minimum variance (STMV) algorithm is a kind of high resolution beam-forming algorithm which holds the lower side lobe and narrower main lobe advantages.It could be concluded that its calculation cost has direct ratio with the cube of sensors number M. When the towed line array's sensors number M is larger, the calculation cost of STMV algorithm is much more which limited its application. Considering this limitation, combining the integral function of one-order recursive filter with iterative formula of the inverse matrix, STMV iterative algorithm is proposed in the dissertation, and its calculation cost has direct ratio with M2 approximately. Simulation results showed iterative algorithm could reduce the calculation cost, meanwhile could preserve the high resolution and weak signal detection characteristics of STMV synchronously. When applied in experiment of 48 sensors line array, the calculation cost is reduced to 1/24 of original algorithm, which is much easier for its real-time realization. Meanwhile the proposed algorithm can estimate each target's azimuth even when the sources'power differs in large scales or the sources azimuths are adjacent.