Peixuan Yang

The range-Doppler (RD) technique is extensively utilized by the advanced imaging sonar that features the resolution regardless of range and frequency. Unluckily, the focusing performances are mainly limited by two factors when classical RD techniques are extended to the multireceiver synthetic aperture sonar (SAS). The primary factor lies in the developments of spectrum by using the approximation of range, which brings the range error. To design the RD algorithm, the Taylor approximation of spectrum which must be carried out brings extra phase error. Both errors would limit the focusing performance of multireceiver SAS system. To strength the performance, a new RD technique is offered with this work. In accordance with the one-by-one mapping between the sonar bearing angle and azimuth Doppler frequency, an approximated range including the monostatic equivalent range and bearing angle dependent range error is proposed. The presented model shows much higher accuracy than traditional range models. After correcting the bearing angle dependent error via the multiplication and interpolation, the datasets are viewed to be the monostatic equivalent signal. Then, an advanced RD algorithm correcting the phase error of approximated spectrum is provided. In comparison with conventional approaches, the proposed approach is efficient and owns the potential to improve the focusing performance. The computer simulations and experiments based on SAS datasets further indicate that the proposed RD technique owns the ability to achieve much more outstanding images than conventional approaches.

Traditional imaging algorithm of multireceiver synthetic aperture sonar based on Loffeld’s bistatic formula (LBF) suffers from a tradeoff between focusing performance and efficiency due to the spatial variance of LBF. To improve the performance and efficiency, we develop a chirp scaling (CS) algorithm based on the reformulated LBF, which includes the range-variant and range-invariant terms. The phase error caused by LBF reformulation and range-invariant term are first compensated. Since the range-variant term used for the design of the CS algorithm is weighted by a factor, all filter functions of CS algorithm are newly deduced. Based on these improvements, the sub-block width is allowed to be enlarged. Consequently, both the efficiency and performance are improved. Numerical results show that the ghost suppression performance of our method is improved nearly 10 dB compared to traditional method. Besides, our method is more time-saving than traditional method.

Classic multireceiver synthetic sonar (SAS) reconstruction algorithms relying upon Loffeld’s bistatic formula (LBF) should firstly utilize the data segmentation approach to remove the multireceiver deformation (MD) term. Usually, the small sub-block is required by traditional LBF based imaging algorithms to produce the high performance result. To address this issue, we describe a receiver-by-receiver based imaging algorithm. The presented method firstly reformulates the original LBF to range dependent and independent terms. Then, the image reconstruction receiver-by-receiver is carried out. The LBF reformulation and the quadratic expansion of range-dependent term needed by subsequent range-Doppler (RD) algorithm would generate approximation error corrected by data segmentation approach in frequency domain. After performing the range cell migration correction (RCMC) receiver-by-receiver, the signal in range-Doppler domain related to each receiver is coherently synthesized, and the azimuth offset is thereafter corrected. The focusing result would be produced when the azimuth inverse Fourier transform (IFT) is completed. On the basis of simulation and real data test experiments, conventional focusing approach with wide sub-block is seriously affected by ghost targets, which are successfully avoided by presented method with the same wide sub-block. It indicates that the presented method relaxes the requirement for the sub-block width.

Before directly using imaging algorithms based on monostatic synthetic aperture sonar (SAS), the phase center approximation (PCA) is used to transform multireceiver SAS data to monostatic SAS equivalent signal. This operation often contains phase compensation and interpolation. However, the space variance of phase error makes the equivalent conversion a challenge. This paper develops a generalized PCA model considering the space variance of approximation error. Traditional PCA models are just the simplification of the presented model. With our preprocessing step, the space-variant phase error is compensated by using sub-block processing approach instead of interpolation. Then any imaging algorithms designed for conventional SAS are directly used. Based on simulations, the focused images of traditional PCA method would suffer from image distortion, which is successfully avoided by the presented algorithm.

The back projection (BP) algorithm is characterized by its high performance for multi-receiver synthetic aperture sonar (SAS). For this reason, it is usually used to evaluate the imaging performance of Fourier-domain methods. However, this algorithm suffers from a large computation load, and the imaging efficiency is seriously lowered. In order to improve the imaging performance, this paper proposes focusing the multi-receiver SAS data using the BP algorithm based on two interpolators, including the linear interpolation and nearest-neighbor interpolation. The former interpolation is used to decrease the interpolation error based on adjacent sampled data; the latter estimates the data at the desired moment by assigning the data value of the nearest sample as estimated data. Then, the imaging performance of the presented method is discussed in detail based on simulations and real-data processing. With the presented method, the imaging performance can be improved without a loss of efficiency compared to nearest-neighbor interpolation without an upsampling operation. In comparison with the traditional BP algorithm, the presented method can be used to improve the imaging efficiency without any loss of performance.

When the multi-receiver synthetic aperture sonar (SAS) works with a wide-bandwidth signal, the performance of the range-Doppler (R-D) algorithm is seriously affected by two approximation errors, i.e., point target reference spectrum (PTRS) error and residual quadratic coupling error. The former is generated by approximating the PTRS with the second-order term in terms of the instantaneous frequency. The latter is caused by neglecting the cross-track variance of secondary range compression (SRC). In order to improve the imaging performance in the case of wide-bandwidth signals, an improved R-D algorithm is proposed in this paper. With our method, the multi-receiver SAS data is first preprocessed based on the phase center approximation (PCA) method, and the monostatic equivalent data are obtained. Then several sub-blocks are generated in the cross-track dimension. Within each sub-block, the PTRS error and residual quadratic coupling error based on the center range of each sub-block are compensated. After this operation, all sub-blocks are coerced into a new signal, which is free of both approximation errors. Consequently, this new data is used as the input of the traditional R-D algorithm. The processing results of simulated data and real data show that the traditional R-D algorithm is just suitable for an SAS system with a narrow-bandwidth signal. The imaging performance would be seriously distorted when it is applied to an SAS system with a wide-bandwidth signal. Based on the presented method, the SAS data in both cases can be well processed. The imaging performance of the presented method is nearly identical to that of the back-projection (BP) algorithm.

In this paper, we introduce a novel sub-bottom profiler, making good use of the Mills cross configuration of multibeam sonar and synthetic aperture techniques of the synthetic aperture sonar system. The receiver array is mounted along the ship keel, while the transmitter array is mounted perpendicular to the receiver array. With the synthetic aperture technique, the along-track resolution can be greatly improved. The system often suffers from motion error, which severely degrades the imaging performance. To solve this problem, the imaging algorithm with motion compensation (MC) is proposed. With the presented method, the motion error is first estimated based on overlapped elements between successive pulses. Then, the echo data is processed by using the range migration algorithm based on the phase center approximation (PCA) method, which simultaneously performs the MC with the estimated motion error. In order to validate the proposed sub-bottom profiler and data processing method, some simulations and lake trial results are discussed. The processing results of the real data further indicate that the presented configuration has great potential to find buried objects in seabed sediments.