Inshore ship detection is an important research direction of synthetic aperture radar (SAR) images. Due to the effects of speckle noise, land clutters and low signal-to-noise ratio, it is still challenging to achieve effective detection of inshore ships. To solve these issues, an inshore ship detection method based on the level set method and visual saliency is proposed in this paper. First, the image is fast initialized through down-sampling. Second, saliency map is calculated by improved local contrast measure (ILCM). Third, an improved level set method based on saliency map is proposed. The saliency map has a higher signal-to-noise ratio and the local level set method can effectively segment images with intensity inhomogeneity. In this way, the improved level set method has a better segmentation result. Then, candidate targets are obtained after the adaptive threshold. Finally, discrimination is employed to get the final result of ship targets. The experiments on a number of SAR images demonstrate that the proposed method can detect ship targets with reasonable accuracy and integrity.

This paper presents a novel dual-polarized frequency selective rasorber (FSR) with two transmission bands and two absorption bands. The FSR has a 2-D structure composed of a lossy and a lossless frequency selective surface (FSS) layer. The unit cells of the lossy and FSS layer are both arranged to hexagonal periodic structures. The unit cell of the lossy layer is a combination of a loop with loaded resistors and three folded loops. The loop with resistors is located in the center of the unit cell, and surrounded by three folded loops. The equivalent circuit model shows that the two transmission poles are generated by two parallel LC circuits. The two absorption bands located at the lower side of the first transmission pole and between the two transmission poles are generated by series resonances. The FSR realizes two transmission poles at 6.1 GHz and 10.1 GHz, respectively. The reflection coefficient lower than -10 dB ranges from 3.24 to 10.5 GHz. The lower and higher absorption bands with absorption rates greater than 80% range from 3.3 to 4.97 GHz and 7.42 to 9.03 GHz, respectively. A prototype is fabricated and measured to validate our design and the measurement results match well with the simulation results.

Traditional subspace methods which are based on the spatial time-frequency distribution (STFD) matrix have been investigated for direction-of-arrival (DOA) estimation of linear frequency modulation (LFM) signals. However, the DOA estimation performance may degrade substantially when multiple LFM signals are spectrally overlapped in time-frequency (TF) domain. In order to solve this problem, this paper proposes single-source TF points selection algorithm based on Hough transform and short-time Fourier transform (STFT). Firstly, the signal intersections in TF domain can be solved based on the Hough transform, and multiple-source TF points around the intersections are removed, so that the single-source TF points set is reserved. Then, based on the Euclidean distance operator, the single-source TF points set belonging to each signal can be obtained according to the property that TF points of the same signal have same eigenvector. Finally, the averaged STFD matrix is constructed for each signal, and DOA estimation is achieved based on multiple signal classification (MUSIC) algorithm. In this way, the proposed algorithm exhibit remarkable superiority in estimation accuracy and angular resolution over the state-of-the-art schemes and can achieve DOA estimation in the underdetermined cases. In addition, the proposed algorithm can still perform DOA estimation when multiple LFM signals intersect at one point. Numerical simulations demonstrate the validity of the proposed method.

In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm.