We consider an iterative phase synchronization scheme based on maximum a posteriori probability algorithm.In classical approaches,the phase noise estimation model considers one sample per symbol at the channel and rec...We consider an iterative phase synchronization scheme based on maximum a posteriori probability algorithm.In classical approaches,the phase noise estimation model considers one sample per symbol at the channel and receiver.However,information theoretic studies suggested use of more than one sample per symbol at the channel and receiver for achieving higher performance.In this article,a soft-information aided iterative receiver is derived,which uses off-the-shelf blocks for detection and demodulation by keeping the complexity of the receiver acceptable.We consider here two samples per symbols at the channel and receiver in a pragmatic paradigm.It is shown that phase noise estimation can be significantly improved at the expense of modest processing overhead.Simulation results are presented for low-density parity check coded quadrature amplitude modulations.Our results show a significant performance improvement for strong phase noise values compared to classical receiver approaches.展开更多
Mode S Second Surveillance Radar (SSR) is very important means for Air Traffic Control (ATC) now and future,all the responding data which the radar receives need parity processing. Bit and confidence declaration is an...Mode S Second Surveillance Radar (SSR) is very important means for Air Traffic Control (ATC) now and future,all the responding data which the radar receives need parity processing. Bit and confidence declaration is an vital step before error detection and error correction. Based on the commonly used baseline multi-sample algorithm,different conditions are presented and analyzed,the conditions under which error happens are pointed out,and the algorithm in which two statistical variables are added to avoid false declaration. In addition,the moving average method is used to preprocess the sampled data,so as to reduce the influence of noise. The merits the baseline multi-sample technique owes are preserved,and the added computation is small. The declaration veracity is improved,and consequently makes error detection and error correction be facilitated suc-cessfully.展开更多
Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and relocation.It is well known that pre...Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and relocation.It is well known that previous VPR algorithms emphasize the extraction and integration of general image features,while ignoring the mining of salient features that play a key role in the discrimination of VPR tasks.To this end,this paper proposes a Domain-invariant Information Extraction and Optimization Network(DIEONet)for VPR.The core of the algorithm is a newly designed Domain-invariant Information Mining Module(DIMM)and a Multi-sample Joint Triplet Loss(MJT Loss).Specifically,DIMM incorporates the interdependence between different spatial regions of the feature map in the cascaded convolutional unit group,which enhances the model’s attention to the domain-invariant static object class.MJT Loss introduces the“joint processing of multiple samples”mechanism into the original triplet loss,and adds a new distance constraint term for“positive and negative”samples,so that the model can avoid falling into local optimum during training.We demonstrate the effectiveness of our algorithm by conducting extensive experiments on several authoritative benchmarks.In particular,the proposed method achieves the best performance on the TokyoTM dataset with a Recall@1 metric of 92.89%.展开更多
To control water impairment in urban storm- water, it is important to evaluate changing patterns of water quality parameters in stormwater runoff. Thus, the authors performed a series of experiments to investigate the...To control water impairment in urban storm- water, it is important to evaluate changing patterns of water quality parameters in stormwater runoff. Thus, the authors performed a series of experiments to investigate the dynamics of common water parameters during storm events in semi-arid areas, with multiple samples collected and analyzed in field stormwater applications. At this field monitoring site within McAuliffe Park, McAllen, Texas, in the United States, a storm event increased the concentra- tions of Escherichia coli （E. coli）, but this event represented a decreasing trend over the entire event period. Besides, peak intensity of different pollutants in the stormwater runoff occurred at different times other than at any peak flows, representing a complexity of the temporal and spatial measurements. Multi-sample per- event approaches recommended based on the complexity of the hydrograph and different peak intensity times of pollutants. In addition, high bacteria and total suspended solids （TSS） concentrations in the initial stage of the storm event should be considered when designing Best Manage- ment Practices （BMPs） and Low Impact Developments （LIDs）. New strategies and solutions for addressing ecohydrological challenges should be proposed to avoid collateral damages to their both common wealth in ecosystems and human well-beings.展开更多
文摘We consider an iterative phase synchronization scheme based on maximum a posteriori probability algorithm.In classical approaches,the phase noise estimation model considers one sample per symbol at the channel and receiver.However,information theoretic studies suggested use of more than one sample per symbol at the channel and receiver for achieving higher performance.In this article,a soft-information aided iterative receiver is derived,which uses off-the-shelf blocks for detection and demodulation by keeping the complexity of the receiver acceptable.We consider here two samples per symbols at the channel and receiver in a pragmatic paradigm.It is shown that phase noise estimation can be significantly improved at the expense of modest processing overhead.Simulation results are presented for low-density parity check coded quadrature amplitude modulations.Our results show a significant performance improvement for strong phase noise values compared to classical receiver approaches.
文摘Mode S Second Surveillance Radar (SSR) is very important means for Air Traffic Control (ATC) now and future,all the responding data which the radar receives need parity processing. Bit and confidence declaration is an vital step before error detection and error correction. Based on the commonly used baseline multi-sample algorithm,different conditions are presented and analyzed,the conditions under which error happens are pointed out,and the algorithm in which two statistical variables are added to avoid false declaration. In addition,the moving average method is used to preprocess the sampled data,so as to reduce the influence of noise. The merits the baseline multi-sample technique owes are preserved,and the added computation is small. The declaration veracity is improved,and consequently makes error detection and error correction be facilitated suc-cessfully.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region under grant number 2022D01B186.
文摘Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and relocation.It is well known that previous VPR algorithms emphasize the extraction and integration of general image features,while ignoring the mining of salient features that play a key role in the discrimination of VPR tasks.To this end,this paper proposes a Domain-invariant Information Extraction and Optimization Network(DIEONet)for VPR.The core of the algorithm is a newly designed Domain-invariant Information Mining Module(DIMM)and a Multi-sample Joint Triplet Loss(MJT Loss).Specifically,DIMM incorporates the interdependence between different spatial regions of the feature map in the cascaded convolutional unit group,which enhances the model’s attention to the domain-invariant static object class.MJT Loss introduces the“joint processing of multiple samples”mechanism into the original triplet loss,and adds a new distance constraint term for“positive and negative”samples,so that the model can avoid falling into local optimum during training.We demonstrate the effectiveness of our algorithm by conducting extensive experiments on several authoritative benchmarks.In particular,the proposed method achieves the best performance on the TokyoTM dataset with a Recall@1 metric of 92.89%.
文摘To control water impairment in urban storm- water, it is important to evaluate changing patterns of water quality parameters in stormwater runoff. Thus, the authors performed a series of experiments to investigate the dynamics of common water parameters during storm events in semi-arid areas, with multiple samples collected and analyzed in field stormwater applications. At this field monitoring site within McAuliffe Park, McAllen, Texas, in the United States, a storm event increased the concentra- tions of Escherichia coli （E. coli）, but this event represented a decreasing trend over the entire event period. Besides, peak intensity of different pollutants in the stormwater runoff occurred at different times other than at any peak flows, representing a complexity of the temporal and spatial measurements. Multi-sample per- event approaches recommended based on the complexity of the hydrograph and different peak intensity times of pollutants. In addition, high bacteria and total suspended solids （TSS） concentrations in the initial stage of the storm event should be considered when designing Best Manage- ment Practices （BMPs） and Low Impact Developments （LIDs）. New strategies and solutions for addressing ecohydrological challenges should be proposed to avoid collateral damages to their both common wealth in ecosystems and human well-beings.
