Heping Zhong

An Improved Quality-Guided Phase-Unwrapping Algorithm Based on Priority Queue

Phase unwrapping is one of the key problems in reconstructing the elevation map of a scene from interferometric synthetic aperture radar or interferometric synthetic aperture sonar (InSAS) data. In this letter, an improved quality-guided phase-unwrapping algorithm is proposed, which depends on the quality value and its surrounding quality information to guide the path of unwrapping more accurately. In order to design highly efficient quality-guided algorithm, a guided map deduced from the quality map is introduced and taken as the new quality map which the quality-guided algorithm should completely depend on. A quantized quality-guided method is designed, which adopts the quantized new quality map and the priority queue designed to optimize the process of unwrapping. The quantized quality map establishes the relation between the quality values and the indexes of array, which can save the time of inserting one pixel into the priority queue according to its integral quality value. Priority queue keeps all the pixels by their quantized quality in a nondecreasing order by maintaining the doubly linked lists in an increasing order. An optimized strategy is used to accelerate the process of finding the pixel with the highest quality value in the priority queue. Tests performed on real InSAS data and simulated interferograms confirm the accuracy and efficiency of the proposed algorithm, and the improved algorithm is suitable for our real-time processing InSAS system.

A Quality-Guided and Local Minimum Discontinuity Based Phase Unwrapping Algorithm for InSAR/InSAS Interferograms

Phase unwrapping is one of the key problems in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) or interferometric synthetic aperture sonar (InSAS) data. In this letter, we propose a quality-guided and local minimum discontinuity based phase unwrapping algorithm, which enhances the precision of the unwrapped result by local minimum discontinuity optimization in low quality areas, and still keeps a high efficiency. The new algorithm can be divided into two steps. Firstly, the quality-guided phase unwrapping algorithm is performed on the original wrapped phase image, which helps to remove all the discontinuities caused by the wrapping operation quickly, but tends to spread the unwrapped errors in low quality areas. Secondly, the initial unwrapped result is divided into high and low quality areas according to its quality map, and the minimum discontinuity optimization process is performed in the low quality areas of the initial unwrapped result, which helps to remove the remaining improving loops defined as a loop with more positive jumps than negative ones. This prevents the unwrapped errors spreading from low quality areas to high quality areas and accelerates the optimization process by restricting the optimization place in low quality areas. Tests performed on InSAR and real InSAS data confirm the accuracy and efficiency of the proposed algorithm.

Phase quality map based on local multi-unwrapped results for two-dimensional phase unwrapping.

The efficiency of a phase unwrapping algorithm and the reliability of the corresponding unwrapped result are two key problems in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) or interferometric synthetic aperture sonar (InSAS) data. In this paper, a new phase quality map is designed and implemented in a graphic processing unit (GPU) environment, which greatly accelerates the unwrapping process of the quality-guided algorithm and enhances the correctness of the unwrapped result. In a local wrapped phase window, the center point is selected as the reference point, and then two unwrapped results are computed by integrating in two different simple ways. After the two local unwrapped results are computed, the total difference of the two unwrapped results is regarded as the phase quality value of the center point. In order to accelerate the computing process of the new proposed quality map, we have implemented it in a GPU environment. The wrapped phase data are first uploaded to the memory of a device, and then the kernel function is called in the device to compute the phase quality in parallel by blocks of threads. Unwrapping tests performed on the simulated and real InSAS data confirm the accuracy and efficiency of the proposed method.

Multireceiver Correction for the Chirp Scaling Algorithm in Synthetic Aperture Sonar

The phase center approximation (PCA) and the motion of the receiver array during reception are two main conditions that must be solved to use fast-Fourier-based imaging techniques in multireceiver synthetic aperture sonar (SAS). The former issue affects focusing results at close range while the latter one influences imaging performances in far distance. The processing result is that the uncompensated phase errors, introduced by those two issues, would degrade SAS imaging quality seriously. Through the analysis of outgoing and incoming acoustic paths, this paper derives an improved PCA method, considering the influence under those two approximations, describes the residual effects of narrow-beam approximations for PCA and “stop-and-hop”(S&H) errors in 2-D space domain, and presents imagery processed with chirp scaling (CS) algorithm. Based on the simulation and lake-trial results, the new processing method provides image quality better than conventional algorithms.

Path Following Algorithm for Phase Unwrapping Based on Priority Queue and Quantized Quality Map

Phase unwrapping is the reconstruction of a function of a grid given its values mod 2π , which is a key problem in all quantitative applications of synthetic aperture radar (SAR) interferometry and other related fields. In this paper, a path following algorithm for phase unwrapping based on priority queue and quantized quality map is proposed and tested. A discrete quality map and a priority queue are designed to accelerate the unwrapping process, which can greatly reduce the unwrapping time compared with the conventional quality- guided algorithm. The test performed on real interferometric SAR data confirms the efficiency and accuracy of the proposed algorithm.

Extended Range Doppler Algorithm for Multiple-Receiver Synthetic Aperture Sonar Based on Exact Analytical Two-Dimensional Spectrum

For the imaging of multiple-receiver synthetic aperture sonar (SAS) under the nonstop-hop-stop case, an exact analytical solution for the two-dimensional (2-D) frequency spectrum is usually difficult to obtain because of the existence of the double-square-root (DSR) term in the range history equation. Several approximate solutions for the 2-D spectrum have been derived to focus the multiple-receiver SAS data. In this paper, the range history geometry for multiple-receiver SAS is newly constructed to meet the demand of the derivation of an analytical 2-D spectrum. According to the geometry-based bistatic formula (GBF) method, a quasi-analytical 2-D spectrum with an unknown variable named half quasi-bistatic angle (HQBA) is reviewed. Based on the method of series reversion (MSR), the fourth order equation with respect to the HQBA is solved and an analytical HQBA is obtained. After substituting the analytical HQBA into the quasi-analytical 2-D spectrum, a completely analytical 2-D spectrum is obtained and the problem of the 2-D spectrum derivation caused by the DSR term is solved successfully. In this paper, an extended range Doppler (RD) algorithm based on the derived 2-D spectrum is proposed for focusing the multiple-receiver SAS data under the non stop-hop-stop case. The results of simulation and real experiment data imaging have validated the effectiveness and accuracy of the proposed algorithm.

Multibaseline InSAR interferometric phase estimation using COMET-EXIP method

In this paper, borrowing the idea of distributed source model in direction-of-arrival (DOA) estimation, a novel distributed pixel model is proposed for multibaseline InSAR absolute phase estimation. And the COvariance Matching Estimation Techniques-Extend Invariance Principle (COMET-EXIP) method is used to estimate the absolute interferometric phase for multibaseline InSAR. The proposed method can provide a robust unwrapped interferometric phase even in the presence of the large image coregistration. Some simulation results verify the performance of the proposed method.

Corrections to “An Improved Quality-Guided Phase-Unwrapping Algorithm Based on Priority Queue” [Mar 11 364-368]

In the above letter (ibid., vol. 8, no. 2, pp. 364-368, Mar. 2011), in the Abstract, a sentence is incorrect. The correct sentence is presented here.