A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and d...A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and diagonal loading technique, and it uses the framework of the adaptive coherence estimator （ACE）. It can effectively detect a target with low sample support. Compared with its natural competitors, the novel detector has higher proba- bility of detection （PD）, especially when the number of the training data is low. Moreover, it is shown to be practically constant false alarm rate （CFAR）.展开更多
The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can c...The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can control the degree to which the mismatched signals are rejected. Remarkably, it is found that they both cover existing famous detectors as their special cases. More importantly, they possess the constant false alarm rate（CFAR）property and achieve enhanced mismatched signal rejection or improved robustness than their natural competitors. Besides, they can provide slightly better matched signals detection performance than the existing detectors.展开更多
Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors （ACE...Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors （ACE） of model is developed in this paper. The ACE can combine effectively statistical and dynamical methods, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasonably absorb the information of a great many analogues in historical data in order to reduce model errors and improve forecast skill. Purthermore, the ACE may identify specific historical data for the solution of the inverse problem in terms of the particularity of current forecast. The qualitative analyses show that the ACE is theoretically equivalent to the principle of the previous analogue-dynamical model, but need not rebuild the complicated analogue-deviation model, so has better feasibility and operational foreground. Moreover, under the ideal situations, when numerical models or historical analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.展开更多
Swimming is excellent exercise and offers many health benefits. However, the ＂chlorine smell＂ in swimming pools may be a turn-off for some people. Although this smell is often thought to be of chlorine, it actually ...Swimming is excellent exercise and offers many health benefits. However, the ＂chlorine smell＂ in swimming pools may be a turn-off for some people. Although this smell is often thought to be of chlorine, it actually comes from volatile compounds that are produced from unintended reactions between disinfectants （e.g., chlorine） and organic matter in the water （Li and Blatchley, 2007; Zwiener et al., 2007; Schmalz et al., 2011; Daiber et al., 2016）. Body fluids, such as sweat and urine, are among the sources of this organic matter that contribute to the formation of disinfection byproducts （DBPs） （Richardson et al., 2007; Arnaud, 2016; Tang et al., 2016）.展开更多
基金supported by the National Natural Science Foundation of China(609250056110216961501505)
文摘A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and diagonal loading technique, and it uses the framework of the adaptive coherence estimator （ACE）. It can effectively detect a target with low sample support. Compared with its natural competitors, the novel detector has higher proba- bility of detection （PD）, especially when the number of the training data is low. Moreover, it is shown to be practically constant false alarm rate （CFAR）.
基金supported by the National Natural Science Foundation of China(6110216960925005)
文摘The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can control the degree to which the mismatched signals are rejected. Remarkably, it is found that they both cover existing famous detectors as their special cases. More importantly, they possess the constant false alarm rate（CFAR）property and achieve enhanced mismatched signal rejection or improved robustness than their natural competitors. Besides, they can provide slightly better matched signals detection performance than the existing detectors.
基金Supported jointly by the National Natural Science Foundation of China under Grant Nos. 40233031, 40575036 and 40675039.
文摘Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors （ACE） of model is developed in this paper. The ACE can combine effectively statistical and dynamical methods, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasonably absorb the information of a great many analogues in historical data in order to reduce model errors and improve forecast skill. Purthermore, the ACE may identify specific historical data for the solution of the inverse problem in terms of the particularity of current forecast. The qualitative analyses show that the ACE is theoretically equivalent to the principle of the previous analogue-dynamical model, but need not rebuild the complicated analogue-deviation model, so has better feasibility and operational foreground. Moreover, under the ideal situations, when numerical models or historical analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.
文摘Swimming is excellent exercise and offers many health benefits. However, the ＂chlorine smell＂ in swimming pools may be a turn-off for some people. Although this smell is often thought to be of chlorine, it actually comes from volatile compounds that are produced from unintended reactions between disinfectants （e.g., chlorine） and organic matter in the water （Li and Blatchley, 2007; Zwiener et al., 2007; Schmalz et al., 2011; Daiber et al., 2016）. Body fluids, such as sweat and urine, are among the sources of this organic matter that contribute to the formation of disinfection byproducts （DBPs） （Richardson et al., 2007; Arnaud, 2016; Tang et al., 2016）.
