High Frequency Surface Wave Radar (HFSWR) can perform the functions of ocean environment monitoring, target detection, and target tracking over the horizon. However, its system's performance is always limited by the severe ionospheric clutter environment, especially by the nonhomogeneous component. The nonhomogeneous ionospheric clutter generally can cover a few Doppler shift units and a few angle units. Consequently, weak targets masked by the nonhomogeneous ionospheric clutter are difficult to be detected. In this paper, a novel algorithm based on angle-Doppler joint eigenvector which considers the angle-Doppler map of radar echoes is adopted to analyze the characteristics of the nonhomogeneous ionospheric clutter. Given the measured data set, we first investigate the correlation between the signal of interest (SOI) and the nonhomogeneous ionospheric clutter and then the correlation between the nonhomogeneous ionospheric clutters in different two ranges. Finally, a new strategy of training data selection is proposed to improve the joint domain localised (JDL) algorithm. Simulation results show that the improved-JDL algorithm is effective and the performance of weak target detection within nonhomogeneous ionospheric clutter is improved.
Scintillators enable invisible X-ray to be converted
into ultraviolet
(UV)/visible light that can be collected using a sensor array and
is the core component of the X-ray imaging system. However, combining
the excellent properties of high light output, high spatial resolution,
flexibility, non-toxicity, and cost effectiveness into a single X-ray
scintillator remains a great challenge. Herein, a novel scintillator
based on benzyltriphenylphosphonium manganese(II) bromide (BTP2MnBr4) nanocrystal (NC) membranes was developed
by the in situ fabrication strategy. The long Mn–Mn distance
provided by the large BTP cation allows the nonradiative energy dissipation
in this manganese(II) halide to be significantly suppressed. As a
result, the flexible BTP2MnBr4 NC scintillator
shows an excellent linear response to the X-ray dose rate, a high
light yield of ∼71,000 photon/MeV, a low detection limit of
86.2 nGyair/s at a signal-to-noise ratio of 3, a strong
radiation hardness, and a long-term thermal stability. Thanks to the
low Rayleigh scattering associated with the dense distribution of
nanometer-scale emitters, light cross-talk in X-ray imaging is greatly
suppressed. The impressively high-spatial resolution X-ray imaging
(23.8 lp/mm at modulation transfer function = 0.2 and >20 lp/mm
for
a standard pattern chart) was achieved on this scintillator. Moreover,
well-resolved 3D dynamic rendering X-ray projections were also successfully
demonstrated using this scintillator. These results shed light on
designing efficient, flexible, and eco-friendly scintillators for
high-resolution X-ray imaging.
Oblique projection polarization filter (OPPF) can be applied as an effective approach for interference cancellation in high-frequency surface wave radar (HFSWR) and other systems. In order to suppress the nonstationary ionosphere clutter further, a novel OPPF based clutter suppressing scheme is proposed in this paper. The polarization and nonstationary characteristic of the clutter are taken into account in the algorithms referred to as range-Doppler domain polarization suppression (RDDPS) and the range-time domain polarization suppression (RTDPS) method, respectively. The RDDPS is designed for weak ionosphere clutter and implemented in the range-Doppler domain directly, whereas the RTDPS algorithm is designed to suppress the powerful ionosphere clutter with a multisegment estimation and suppression scheme. About 15–23 dB signal to interference ratio (SIR) improvement can be excepted when using the proposed method, whereas the targets can be more easily detected in the range-Doppler map. Experimental results demonstrate that the scheme proposed is effective for nonstationary ionosphere clutter and is proven to be a practical interference cancellation technique for HFSWR.
The use of ℓ p ( 0 < p < 1 ) norm minimization will improve array diagnosis performance provided that the issue of local minima associated to its non-convex nature is properly handled. In order to overcome this deficiency, a hybrid method using random perturbation and non-convex optimization is investigated in this paper. Although it acquires a higher computational time, the trade-off between an accurate diagnosis and the computational burden appears to be acceptable. Theoretical analysis and simulation results demonstrate that the proposed method overcomes this disadvantage effectively and achieves better performance compared to the standard ℓ 1 norm minimization with a smaller number of far-field measurements, suggesting that the proposed method can be used to improve the performance of array diagnosis.
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