Huang Jian-guo

Orthogonal waveforms design and performance analysis for MIMO sonar

In this paper, a Multiple-Input Multiple-Output (MIMO) sonar system which can deal with multiple targets is discussed, where orthogonal waveforms are transmitted simultaneously. According to the requirement of waveform orthogonality, the orthogonal frequency division pseudo-random signal (OFD-PR), orthogonal frequency division determinant signal (OFD-LFM) and the spread-spectrum code-based signal (Gold-BPSK) are designed. The Maximum Likelihood (ML) DOA estimator and CRB for MIMO sonar is described. The performance of MIMO sonar based on different waveforms is analyzed via experiments in an anechoic water tank. Simulation and experimental results show that the waveforms which we design possess the higher resolution for multiple source DOA estimation than its phased-array and they could resolve the two targets with a separation of 1/2 beam width at low SNR. The analysis of DOA estimates and experimental results show that the OFD-PR signal has much better performance than others.

Implementation of an OFDM underwater acoustic communication system on an underwater vehicle with multiprocessor structure

Orthogonal frequency division multiplexing (OFDM) can fully use the frequency band and transmit data at high speeds. The ADSP-TS101 is a high performance digital signal processor (DSP) with good properties that include parallel processing and a high speed. Aimed at the real-time processing requirement of the OFDM algorithm, an underwater acoustic communication system with real-time processing capability is carried out. The system is mainly composed of multiple ADSP-TS101s, a multi-channel synchronous sample module and a field programmable gate array (FPGA) chip. The multiprocessor structure is made up of a cluster/data flow associated multiprocessing parallel processing structure as the operation kernel, and a multi-channel synchronous sample module is designed to realize no phase warp among the multiple channels’ data at the same time. The digital modulation/demodulation methods are applied to the OFDM algorithm. Through experiments in a lake, the results show that the system has good stability and real-time processing capability, thus satisfying the design requirements.

Wideband transmit beampattern design for MIMO array

Transmit beamforming design for Multiple Input Multiple Output (MIMO) array is studied. The performance of narrowband transmits beamforming design methods is detailed discussed through simulations. Aiming at wideband transmit beamforming design; suppose each sensor transmits at the same power level, three criteria namely conventional least square beampattern matching, minimum targets azimuth cross-correlation matching and minimum sidelobe matching are proposed to constrain the cross-relation matrix of wideband transmitting signals. Through equivalent transform, above optimum problems are described as Semi-Definite Quadratic Programming. Convex optimization techniques are used to find the numerical solution of the resulted optimization problems. Simulations show that our method is effective and promising.

Detection of the number of signals by a threshold based on peak-to-average ratio

Source number is a crucial factor in array signal processing. A new method is present here to estimate the source number. The array output data is firstly weighted by the eigenvectors of the covariance matrix, and then the peak-to-average power ratio (PAR) of the weighted data is computed. The inherent properties of the PAR are exploited. A new multiple targets detection threshold criterion: peak-to-average power ratio threshold criterion (PARTC) is established by concerning the inherent properties of the PAR. Simulation results show that PARTC method performs better than AIC and MDL under all conditions.

Study on the long-distance target apperception techniques for underwater vehicles

Abstract The limited physical size for autonomous underwater vehicles (AUV) or unmanned underwater vehicles (UUV) makes it difficult to acquire enough space gain for localizing long-distance targets. A new technique about long-distance target apperception with passive synthetic aperture array for underwater vehicles is presented. First, a synthetic aperture-processing algorithm based on the FFT transform in the beam space (BSSAP) is introduced. Then, the study on the flank array passive long-distance apperception techniques in the frequency scope of 11–18 kHz is implemented from the view of improving array gains, detection probability and augmenting detected range under a certain sea environment. The results show that the BSSAP algorithm can extend the aperture effectively and improve detection probability. Because of the augment of the transmission loss, the detected range has the trend of decline with the increase of frequency under the same target source level. The synthesized array could improve the space gain by nearly 7 dB and SNR is increased by about 5 dB. The detected range is enhanced to nearly 2 km under the condition of 108–118 dB of the target source level for AUV system in measurement interval of nearly 1 s.

Extended Kalman filtering-based channel estimation for space-time coded MIMO-OFDM systems

A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based (EKF-based) channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square (LS) and the least mean square (LMS) methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer dramatic system performance improvement at a modest cost of computational complexity.

Channel estimation for MIMO-OFDM systems in rapid fading channels

A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multiple-output (MIMO-OFDM) in rapid fading channels is proposed. This approach combines the advantages of an optimal training sequence based least-square (OLS) algorithm and an expectation-maximization (EM) algorithm. The channels at the training blocks are estimated using an estimator based on the OLS algorithm. To compensate for the fast Rayleigh fading at the data blocks, a time domain based Gaussian interpolation filter is presented. Furthermore, an EM algorithm is introduced to improve the performance of channel estimation by a few iterations. Simulations show that this channel estimation approach can effectively track rapid channel variation.

An improved hypothesis-feedback equalization algorithm for multicode direct-sequence spread-spectrum underwater communications

In underwater acoustic communication, because the available bandwidth of the channel is severely limited, the direct-sequence spread-spectrum scheme can only be realized at low bit rates. To improve the transmission speed, a multicode spread-spectrum scheme is considered. However, in this case, due to the rapid time-variability of the underwater channel, and the influence of inter-symbol interference (ISI) and inter-channel interference (ICI), the conventional rake receiver may fail to function. The hypothesis-feedback equalization algorithm has been proposed for the direct-sequence spread-spectrum system [1]. By updating coefficients at chip rate and feeding back hypothesized chips, it can track time-variability and combat ISI effectively. However, for a multicode system, its performance will be degraded by ICI. An improved algorithm is proposed in this paper, which combines parallel interference cancellation (PIC) with hypothesis-feedback equalization (HFE), with the capabilities of tracking the time-varying channel and suppressing the ISI and ICI at the same time. Simulation results prove that the proposed algorithm can significantly improve the performance of a multicode system.

Sparse sample matrix inversion with diagonal loading for reverberation suppression

The main problem of active sonar detection is that the reverberation has spatial and temporal two-dimensional coupling characteristic which is similar to clutters in airborne radar. This paper presents a sparse sample matrix inversion with diagonal loading (SSMI-DL) for reverberation suppression in active sonar. The proposed method transfers Pulse Doppler radar STAP processing techniques into active sonar application, which utilizes the inverse reverberation covariance matrix to obtain adaptive weights and avoids singular reverberation covariance matrix with diagonal loading due to limited available received data. Simulation results are provided to verify that the SSMI-DL is more effective for improving slowly moving target detection for CW pulse than the conventional methods.

Study on algorithms for fast frequency estimation in the system of high-speed underwater acoustic communication

Aiming at the requirement of fast frequency estimation for high-speed underwater acoustic communication, an improved algorithm for fast frequency estimation with short sequences is proposed based on the algorithm of three-point self-correlation. Increasing a sampling data is adopted for the improved algorithm of fast frequency estimation. The precision of frequency estimation is improved, but the operation amount is almost equal to the ones of the other algorithm. The simulation results show that the Root Mean Square (RMS) of the improved algorithm is closer to Cramer-Rao Bound (CRB) than the ones of the other algorithm. Whats more, the RMS of the improved algorithm outperform the ones of the other method by 10dB in the environment with low signal-noise-ratio (SNR), and it is better for the higher frequency signal with the same SNR, and the RMS can reach the CRB while the SNR is increased to 10dB at the condition of 6kHz frequency signal.