High frequency surface wave radar (HFSWR) is well proved to have over the horizon (OTH) detection capability to weak aerial targets, such as concealed airplanes or cruise missiles. The most important problem of detect...High frequency surface wave radar (HFSWR) is well proved to have over the horizon (OTH) detection capability to weak aerial targets, such as concealed airplanes or cruise missiles. The most important problem of detection of fast and small targets using HFSWR is earlier warning, i.e. enlargement of detection range oftargets. Therefore, the detection threshold should be decreased as low as possible, but numerous false alarms are brought about at the same time. On this condition, conventional track initiation techniques, which normally require the probability of false alarm to be at the level of 10-6, will initiate enormous false tracks and lead to abnormal operation of tracking system. An adaptive modified hough transform (AMHT) track initiator is proposed accordingly and the relation of detection range to the performance of track initiator is analyzed in this paper. Simulations are performed to confirm the capability of track initiation to fast and small targets in dense clutter by AMHT track initiator. The tolerable probability of false alarm of detector can reach the level of 10 -3 . And it performs better than track initiator based on modified hough transform (MHT).展开更多
When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competitio...When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competition strategy algorithm” is presented. In this method, initial measurements give birth to several particle groups around them, regularly. Each of the groups is tested several times, separately, in the beginning periods, and the group that has the most number of efficient particles is selected as the initial particles. For this method, sample initial particles selected are on the basis of several measurements instead of only one first measurement, which surely improves the accuracy of initial particles. The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greatly improves the accuracy of initial particles, which makes the effect of filtering much better.展开更多
Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction s...Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Ni n？o prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Ni n？o prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year,increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.展开更多
Initial errors in the tropical Indian Ocean(IO-related initial errors) that are most likely to yield the Spring Prediction Barrier(SPB) for La Ni?a forecasts are explored by using the CESM model.These initial errors c...Initial errors in the tropical Indian Ocean(IO-related initial errors) that are most likely to yield the Spring Prediction Barrier(SPB) for La Ni?a forecasts are explored by using the CESM model.These initial errors can be classified into two types.Type-1 initial error consists of positive sea temperature errors in the western Indian Ocean and negative sea temperature errors in the eastern Indian Ocean,while the spatial structure of Type-2 initial error is nearly opposite.Both kinds of IO-related initial errors induce positive prediction errors of sea temperature in the Pacific Ocean,leading to underprediction of La Nina events.Type-1 initial error in the tropical Indian Ocean mainly influences the SSTA in the tropical Pacific Ocean via atmospheric bridge,leading to the development of localized sea temperature errors in the eastern Pacific Ocean.However,for Type-2 initial error,its positive sea temperature errors in the eastern Indian Ocean can induce downwelling error and influence La Ni?a predictions through an oceanic channel called Indonesian Throughflow.Based on the location of largest SPB-related initial errors,the sensitive area in the tropical Indian Ocean for La Nina predictions is identified.Furthermore,sensitivity experiments show that applying targeted observations in this sensitive area is very useful in decreasing prediction errors of La Nina.Therefore,adopting a targeted observation strategy in the tropical Indian Ocean is a promising approach toward increasing ENSO prediction skill.展开更多
The past 40 years has seen the remarkable history of the building of not only socialism with Chinese characteristics but also a moderately prosperous society by the Chinese people led by the Communist Party of China.B...The past 40 years has seen the remarkable history of the building of not only socialism with Chinese characteristics but also a moderately prosperous society by the Chinese people led by the Communist Party of China.By 2020,China will have finished building a moderately prosperous society in all respects and realized the second strategic objective of the rejuvenation of the Chinese nation.展开更多
By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Oce...By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Ocean Dipole events were identified. The initial errors cause a significant winter predictability barrier(WPB) or summer predictability barrier(SPB).The WPB is closely related with the initial errors in the tropical Indian Ocean, where two types of WPB-related initial errors display opposite patterns and a west–east dipole. In contrast, the occurrence of the SPB is mainly caused by initial errors in the tropical Pacific Ocean, where two types of SPB-related initial errors exhibit opposite patterns, with one pole in the subsurface western Pacific Ocean and the other in the upper eastern Pacific Ocean. Both of the WPB-related initial errors grow the fastest in winter, because the coupled system is at its weakest, and finally cause a significant WPB. The SPB-related initial errors develop into a La Ni ?na–like mode in the Pacific Ocean. The negative SST errors in the Pacific Ocean induce westerly wind anomalies in the Indian Ocean by modulating the Walker circulation in the tropical oceans. The westerly wind anomalies first cool the sea surface water in the eastern Indian Ocean. When the climatological wind direction reverses in summer, the wind anomalies in turn warm the sea surface water, finally causing a significant SPB. Therefore, in addition to the spatial patterns of the initial errors, the climatological conditions also play an important role in causing a significant predictability barrier.展开更多
To fabricate the comb target with low damping and high performance-price ratio,0.03-\{0.1 mm\} thickness aluminum foi l used as the conducting medium,the upper and lower surfaces covered with 0.5-1 mm thickness plasti...To fabricate the comb target with low damping and high performance-price ratio,0.03-\{0.1 mm\} thickness aluminum foi l used as the conducting medium,the upper and lower surfaces covered with 0.5-1 mm thickness plastic film,after four processes of thrusting,laminating,punching and cu tting,a 500 mm×\{500 mm\} comb target is fabricated.A 155-mm projectile expl osiv e pow er test is conducted.Using the newly fabricated comb target,the measured initi al velocity of the fragment is 2 070 m/s.Th e test results show that the new comb target is of high test pre cision,small damping,low cost and high production efficiency,and it can measure th e 2 mm×2 m m fragment's initial velocity.展开更多
Using the outputs from CMCC-CM in CMIP5 experiments,the authors identified sensitive areas for targeted observations in ENSO forecasting from the perspective of the initial error growth(IEG)method and the particle fil...Using the outputs from CMCC-CM in CMIP5 experiments,the authors identified sensitive areas for targeted observations in ENSO forecasting from the perspective of the initial error growth(IEG)method and the particle filter(PF)method.Results showed that the PF targets areas over the central-eastern equatorial Pacific,while the sensitive areas determined by the IEG method are slightly to the east of the former.Although a small part of the areas targeted by the IEG method also lie in the southeast equatorial Pacific,this does not affect the large-scale overlapping of the sensitive areas determined by these two methods in the eastern equatorial Pacific.Therefore,sensitive areas determined by the two methods are mutually supportive.When considering the uncertainty of methods for determining sensitive areas in realistic targeted observation,it is more reasonable to choose the above overlapping areas as sensitive areas for ENSO forecasting.This result provides scientific guidance for how to better determine sensitive areas for ENSO forecasting.展开更多
Tandem-based learning is a way of collaborative learning with which two different language users communicate in theirtarget language. It implies that the both learners play a role as a teacher and learner. Through suf...Tandem-based learning is a way of collaborative learning with which two different language users communicate in theirtarget language. It implies that the both learners play a role as a teacher and learner. Through sufficient cooperative duration andexposure to their target language learning, their interest and motivation of translation majors were noticeably inspired. This programis sure to be very effective for foreign language learning, if the two principles are followed: principle of reciprocity and self-initia-tive.展开更多
文摘High frequency surface wave radar (HFSWR) is well proved to have over the horizon (OTH) detection capability to weak aerial targets, such as concealed airplanes or cruise missiles. The most important problem of detection of fast and small targets using HFSWR is earlier warning, i.e. enlargement of detection range oftargets. Therefore, the detection threshold should be decreased as low as possible, but numerous false alarms are brought about at the same time. On this condition, conventional track initiation techniques, which normally require the probability of false alarm to be at the level of 10-6, will initiate enormous false tracks and lead to abnormal operation of tracking system. An adaptive modified hough transform (AMHT) track initiator is proposed accordingly and the relation of detection range to the performance of track initiator is analyzed in this paper. Simulations are performed to confirm the capability of track initiation to fast and small targets in dense clutter by AMHT track initiator. The tolerable probability of false alarm of detector can reach the level of 10 -3 . And it performs better than track initiator based on modified hough transform (MHT).
基金the National Natural Science Foundation of China (60572038).
文摘When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competition strategy algorithm” is presented. In this method, initial measurements give birth to several particle groups around them, regularly. Each of the groups is tested several times, separately, in the beginning periods, and the group that has the most number of efficient particles is selected as the initial particles. For this method, sample initial particles selected are on the basis of several measurements instead of only one first measurement, which surely improves the accuracy of initial particles. The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greatly improves the accuracy of initial particles, which makes the effect of filtering much better.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19060102)the National Natural Science Foundation of China (Grant Nos. 41475101, 41690122, 41690120 and 41421005)the National Programme on Global Change and Air–Sea Interaction Interaction (Grant Nos. GASI-IPOVAI-06 and GASI-IPOVAI-01-01)
文摘Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Ni n？o prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Ni n？o prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year,increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.
基金supported by the National Key R&D Program of China (Grant No.2019YFC1408004)together with the National Natural Science Foundation of China (Grant Nos.41930971,41805069,41606031)the Office of China Postdoctoral Council (OCPC) under Award Number 20190003。
文摘Initial errors in the tropical Indian Ocean(IO-related initial errors) that are most likely to yield the Spring Prediction Barrier(SPB) for La Ni?a forecasts are explored by using the CESM model.These initial errors can be classified into two types.Type-1 initial error consists of positive sea temperature errors in the western Indian Ocean and negative sea temperature errors in the eastern Indian Ocean,while the spatial structure of Type-2 initial error is nearly opposite.Both kinds of IO-related initial errors induce positive prediction errors of sea temperature in the Pacific Ocean,leading to underprediction of La Nina events.Type-1 initial error in the tropical Indian Ocean mainly influences the SSTA in the tropical Pacific Ocean via atmospheric bridge,leading to the development of localized sea temperature errors in the eastern Pacific Ocean.However,for Type-2 initial error,its positive sea temperature errors in the eastern Indian Ocean can induce downwelling error and influence La Ni?a predictions through an oceanic channel called Indonesian Throughflow.Based on the location of largest SPB-related initial errors,the sensitive area in the tropical Indian Ocean for La Nina predictions is identified.Furthermore,sensitivity experiments show that applying targeted observations in this sensitive area is very useful in decreasing prediction errors of La Nina.Therefore,adopting a targeted observation strategy in the tropical Indian Ocean is a promising approach toward increasing ENSO prediction skill.
文摘The past 40 years has seen the remarkable history of the building of not only socialism with Chinese characteristics but also a moderately prosperous society by the Chinese people led by the Communist Party of China.By 2020,China will have finished building a moderately prosperous society in all respects and realized the second strategic objective of the rejuvenation of the Chinese nation.
基金jointly sponsored by the National Natural Science Foundation of China (Grant Nos. 41506032 and 41530961)the National Programme on Global Change and Air–Sea Interaction (Grant No. GASI-IPOVAI-06)
文摘By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Ocean Dipole events were identified. The initial errors cause a significant winter predictability barrier(WPB) or summer predictability barrier(SPB).The WPB is closely related with the initial errors in the tropical Indian Ocean, where two types of WPB-related initial errors display opposite patterns and a west–east dipole. In contrast, the occurrence of the SPB is mainly caused by initial errors in the tropical Pacific Ocean, where two types of SPB-related initial errors exhibit opposite patterns, with one pole in the subsurface western Pacific Ocean and the other in the upper eastern Pacific Ocean. Both of the WPB-related initial errors grow the fastest in winter, because the coupled system is at its weakest, and finally cause a significant WPB. The SPB-related initial errors develop into a La Ni ?na–like mode in the Pacific Ocean. The negative SST errors in the Pacific Ocean induce westerly wind anomalies in the Indian Ocean by modulating the Walker circulation in the tropical oceans. The westerly wind anomalies first cool the sea surface water in the eastern Indian Ocean. When the climatological wind direction reverses in summer, the wind anomalies in turn warm the sea surface water, finally causing a significant SPB. Therefore, in addition to the spatial patterns of the initial errors, the climatological conditions also play an important role in causing a significant predictability barrier.
文摘To fabricate the comb target with low damping and high performance-price ratio,0.03-\{0.1 mm\} thickness aluminum foi l used as the conducting medium,the upper and lower surfaces covered with 0.5-1 mm thickness plastic film,after four processes of thrusting,laminating,punching and cu tting,a 500 mm×\{500 mm\} comb target is fabricated.A 155-mm projectile expl osiv e pow er test is conducted.Using the newly fabricated comb target,the measured initi al velocity of the fragment is 2 070 m/s.Th e test results show that the new comb target is of high test pre cision,small damping,low cost and high production efficiency,and it can measure th e 2 mm×2 m m fragment's initial velocity.
基金supported by the National Natural Science Foundation of China [grant numbers 41930971,41775069,and 41975076]。
文摘Using the outputs from CMCC-CM in CMIP5 experiments,the authors identified sensitive areas for targeted observations in ENSO forecasting from the perspective of the initial error growth(IEG)method and the particle filter(PF)method.Results showed that the PF targets areas over the central-eastern equatorial Pacific,while the sensitive areas determined by the IEG method are slightly to the east of the former.Although a small part of the areas targeted by the IEG method also lie in the southeast equatorial Pacific,this does not affect the large-scale overlapping of the sensitive areas determined by these two methods in the eastern equatorial Pacific.Therefore,sensitive areas determined by the two methods are mutually supportive.When considering the uncertainty of methods for determining sensitive areas in realistic targeted observation,it is more reasonable to choose the above overlapping areas as sensitive areas for ENSO forecasting.This result provides scientific guidance for how to better determine sensitive areas for ENSO forecasting.
文摘Tandem-based learning is a way of collaborative learning with which two different language users communicate in theirtarget language. It implies that the both learners play a role as a teacher and learner. Through sufficient cooperative duration andexposure to their target language learning, their interest and motivation of translation majors were noticeably inspired. This programis sure to be very effective for foreign language learning, if the two principles are followed: principle of reciprocity and self-initia-tive.
