The integer least squares(ILS)estimation is commonly used for carrier phase ambiguity resolution(AR).More recently,the best integer equivariant(BIE)estimation has also attracted an attention for complex application sc...The integer least squares(ILS)estimation is commonly used for carrier phase ambiguity resolution(AR).More recently,the best integer equivariant(BIE)estimation has also attracted an attention for complex application scenarios,which exhibits higher reliability by a weighted fusion of integer candidates.However,traditional BIE estimation with Gaussian distribution(GBIE)faces challenges in fully utilizing the advantages of BIE for urban low-cost positioning,mainly due to the presence of outliers and unmodeled errors.To this end,an improved BIE estimation method with Laplacian distribution(LBIE)is proposed,and several key issues are discussed,including the weight function of LBIE,determination of the candidates included based on the OIA test,and derivation of the variance of LBIE solutions for reliability evaluation.The results show that the proposed LBIE method has the positioning accuracy similar to the BIE using multivariate t-distribution(TBIE),and significantly outperforms the ILS-PAR and GBIE methods.In an urban expressway test with a Huawei Mate40 smartphone,the LBIE method has positioning errors of less than 0.5 m in three directions and obtains over 50%improvements compared to the ILS-PAR and GBIE methods.In an urban canyon test with a low-cost receiver STA8100 produced by STMicroelectronics,the positioning accuracy of LBIE in three directions is 0.112 m,0.107 m,and 0.252 m,respectively,with improvements of 17.6%,27.2%,and 26.1%compared to GBIE,and 23.3%,28.2%,and 30.6%compared to ILS-PAR.Moreover,its computational time increases by 30–40%compared to ILS-PAR and is approximately half of that using TBIE.展开更多
针对现有相关噪声模型—Laplacian模型不能精确描述相关噪声,导致分布式视频编码(DVC,distributed video coding)系统的率失真性能不高的问题,提出像素域DVC中广义伽马分布相关噪声模型。首先分析了相关噪声的统计特性,发现Laplacian分...针对现有相关噪声模型—Laplacian模型不能精确描述相关噪声,导致分布式视频编码(DVC,distributed video coding)系统的率失真性能不高的问题,提出像素域DVC中广义伽马分布相关噪声模型。首先分析了相关噪声的统计特性,发现Laplacian分布的峰值比实际相关噪声分布的低,然后采用广义伽马分布对相关噪声进行拟合,并给出在线估计广义伽马分布参数的方法。实验结果表明,提出的模型能较精确地描述相关噪声,且有效地改善了系统的率失真性能,并减少了解码端计算复杂度。展开更多
1 Introduction The Lévy Laplacian was first introduced by P. Lévy in studying functionals on L^2 [0, 1] and has been investigated by many authors. In the white noise analysis setting Hida first defined L...1 Introduction The Lévy Laplacian was first introduced by P. Lévy in studying functionals on L^2 [0, 1] and has been investigated by many authors. In the white noise analysis setting Hida first defined Lévy Laplacian Δ_L via the second variation of a U-functional and proved that Δ_L annihilates functionals of square integrable (cf. Refs. [3, 4]). InRef. [3], Hida and Sait proved the following formula: Δ_L(?)=-(?)- (Δ_LF)~^, where F is Kuo’s Fourier transform of F. In Ref. [4], according to the original idea of P. Lévy a definition of the Lévy Laplacian was proposed. In the present note we will give a new ex-展开更多
提出一种新的用于H.264/AVC的视频编码失真估计算法.该算法首先使用新的线性关系计算直流系数的方差;然后假设直流系数服从高斯分布,推导出高斯信源在DZ-UTQ with URQ量化器下的失真,根据高斯信源失真和直流系数的方差计算直流系数的编...提出一种新的用于H.264/AVC的视频编码失真估计算法.该算法首先使用新的线性关系计算直流系数的方差;然后假设直流系数服从高斯分布,推导出高斯信源在DZ-UTQ with URQ量化器下的失真,根据高斯信源失真和直流系数的方差计算直流系数的编码失真;再使用一个新函数确定视频编码失真与直流系数编码失真的比值;最后通过该比值和直流系数的编码失真来估计视频编码失真.相比于现有算法中性能最优的算法,新算法可以将平均估计误差降低36%.实验结果表明,新算法能够比现有算法提供更精确的视频编码失真估计.展开更多
基金funded by the National Key R&D Program of China(Grant No.2021YFC3000502)the National Natural Science Foundation of China(Grant No.42274034)+2 种基金the Major Program(JD)of Hubei Province(Grant No.2023BAA026)the Special Fund of Hubei Luojia Laboratory(Grant No.2201000038)the Research project of Chongqing Administration for Marktet Regulation,China(Grant No.CQSJKJ2022037).
文摘The integer least squares(ILS)estimation is commonly used for carrier phase ambiguity resolution(AR).More recently,the best integer equivariant(BIE)estimation has also attracted an attention for complex application scenarios,which exhibits higher reliability by a weighted fusion of integer candidates.However,traditional BIE estimation with Gaussian distribution(GBIE)faces challenges in fully utilizing the advantages of BIE for urban low-cost positioning,mainly due to the presence of outliers and unmodeled errors.To this end,an improved BIE estimation method with Laplacian distribution(LBIE)is proposed,and several key issues are discussed,including the weight function of LBIE,determination of the candidates included based on the OIA test,and derivation of the variance of LBIE solutions for reliability evaluation.The results show that the proposed LBIE method has the positioning accuracy similar to the BIE using multivariate t-distribution(TBIE),and significantly outperforms the ILS-PAR and GBIE methods.In an urban expressway test with a Huawei Mate40 smartphone,the LBIE method has positioning errors of less than 0.5 m in three directions and obtains over 50%improvements compared to the ILS-PAR and GBIE methods.In an urban canyon test with a low-cost receiver STA8100 produced by STMicroelectronics,the positioning accuracy of LBIE in three directions is 0.112 m,0.107 m,and 0.252 m,respectively,with improvements of 17.6%,27.2%,and 26.1%compared to GBIE,and 23.3%,28.2%,and 30.6%compared to ILS-PAR.Moreover,its computational time increases by 30–40%compared to ILS-PAR and is approximately half of that using TBIE.
文摘针对现有相关噪声模型—Laplacian模型不能精确描述相关噪声,导致分布式视频编码(DVC,distributed video coding)系统的率失真性能不高的问题,提出像素域DVC中广义伽马分布相关噪声模型。首先分析了相关噪声的统计特性,发现Laplacian分布的峰值比实际相关噪声分布的低,然后采用广义伽马分布对相关噪声进行拟合,并给出在线估计广义伽马分布参数的方法。实验结果表明,提出的模型能较精确地描述相关噪声,且有效地改善了系统的率失真性能,并减少了解码端计算复杂度。
基金Research supported by the National Natural Science Foundation of China
文摘1 Introduction The Lévy Laplacian was first introduced by P. Lévy in studying functionals on L^2 [0, 1] and has been investigated by many authors. In the white noise analysis setting Hida first defined Lévy Laplacian Δ_L via the second variation of a U-functional and proved that Δ_L annihilates functionals of square integrable (cf. Refs. [3, 4]). InRef. [3], Hida and Sait proved the following formula: Δ_L(?)=-(?)- (Δ_LF)~^, where F is Kuo’s Fourier transform of F. In Ref. [4], according to the original idea of P. Lévy a definition of the Lévy Laplacian was proposed. In the present note we will give a new ex-
文摘提出一种新的用于H.264/AVC的视频编码失真估计算法.该算法首先使用新的线性关系计算直流系数的方差;然后假设直流系数服从高斯分布,推导出高斯信源在DZ-UTQ with URQ量化器下的失真,根据高斯信源失真和直流系数的方差计算直流系数的编码失真;再使用一个新函数确定视频编码失真与直流系数编码失真的比值;最后通过该比值和直流系数的编码失真来估计视频编码失真.相比于现有算法中性能最优的算法,新算法可以将平均估计误差降低36%.实验结果表明,新算法能够比现有算法提供更精确的视频编码失真估计.
