共查询到20条相似文献,搜索用时 156 毫秒
1.
针对复杂环境下运动通信辐射源的无源定位,闭式解方法对于时频差模型中的测量噪声敏感且存在定位均方根误差较大问题.为了改善大观测误差下的定位性能,本文提出一种加权最小二乘联合遗传算法的递推式混合TDOA/FDOA定位方法.该方法首先利用已知站点观测大量时频差数据并建立误差模型,基于模型对定位过程中的多组时频差序列进行数据处理;其次通过加权最小二乘求解目标位置的初始值;然后采用改进的遗传算法在初始值的基础上通过多组时频差序列不断迭代、递推求解,修正位置坐标;最后利用位置估计和频差模型完成对目标速度估计.仿真结果表明,本文定位算法相比于经典两步加权最小二乘法具有更低的均方根误差,在大观测误差下能保持较高精度.同时相比于其他混合定位算法收敛速度快,可以有效减少计算量. 相似文献
2.
本文研究发射机位置未知时的椭圆定位问题,提出了一种低复杂度的目标和发射机位置联合估计的三步闭式求解方法。首先,本文利用直接路径测量值构造一个广义信赖域子问题(Generalized Trust Region Subproblem,GTRS)以得到发射机的估计位置;然后,将所估计的发射机位置代入间接路径模型,以此构造另外一个GTRS 估计目标位置;最后,通过构造线性加权最小二乘问题联合估计目标和发射机的误差项,同时补偿前两步的估计误差,从而进一步提高了定位精度。本文所提算法的三个步骤均存在闭式解,且具有极低的计算复杂度。理论性能分析和仿真验证表明,所提方法的均方误差在大噪声时能够趋近于克拉美-罗下界(Cramer-Rao lower bound,CRLB),在特定环境下与现有方法相比具有更优的性能。 相似文献
3.
4.
为了有效融合多传感器冗余系统量测信息,使状态的估计值更接近于状态的真实值,实现高精度和高可靠性的状态估计,采取了基于最优加权的最小二乘算法、有限窗加权的最小二乘算法和自学习加权最小二乘算法,分别对多传感器实测数据进行融合处理,融合后数据的方差大幅度降低,估计精度显著提高。并与传统的最小二乘算法进行了仿真对比,结果表明,这3种方法较最小二乘算法融合精度更高,其中,自学习加权的最小二乘融合算法既考虑了历史数据的作用,又考虑了环境噪声和新的采样值的影响,增强了对噪声检测的敏感性,估计效果较好。 相似文献
5.
针对浅海探测中激光回波噪声源多、信噪比低,传统非加权最小二乘支持向量机和加权最小二乘支持向量机对低信噪比信号滤波不足的问题,提出将稳健最小二乘法与加权最小二乘支持向量机相结合的滤波方法(HW-LS-SVM)。首先采用强淘汰权函数计算先验权值、残差和均方误差,然后采用权函数模型计算最小二乘支持向量机的权值,最后通过迭代计算实现回波信号滤波。通过仿真实验结果表明, HW-LS-SVM方法较最小二乘支持向量机、贝叶斯最小二乘支持向量机和传统加权最小二乘支持向量机滤波效果更加稳健,在噪声率为45%的情况下,滤波效果较为理想,水面和水底回波提取正确率为100%;对实测4组深水区和4组浅水区数据滤波后提取的海水深度均与背景资料的深度吻合。由此表明, HW-LS-SVM方法具有更好的抗噪性,更适合于对信噪比低的测深激光信号的滤波处理。 相似文献
6.
7.
8.
9.
针对大规模多跳传感器网络节点间所存在的同步误差及其累积误差问题,提出了一种基于加权最小二乘法的TPSN-RBS联合时间同步算法.该算法充分利用可监听到的消息,通过加权最小二乘法估计得到节点逻辑时钟的时间偏移和频率偏移的最优解.用Cramér-Rao下界对本算法进行性能分析,同时与TPSN算法进行仿真对比,结果表明:该算法提高了节点间的同步精度,且在节点密集的大规模无线传感器网络中,在保证较低通信量的同时降低了累积误差. 相似文献
10.
针对传统时差定位闭式解法在量测噪声较大情况下定位性能不佳的缺点,提出了一种新的时差定位算法。该算法首先在无约束条件下利用加权最小二乘得到目标的初始位置估计值,然后利用最大似然方程对初始位置估计值进行校正,校正后的位置估计值将更加接近最大似然估计。通过对算法的仿真分析,结果表明在量测噪声较大的情况下,算法的定位均方误差要小于经典的Chan算法。 相似文献
11.
In this paper, we evaluate the mean square error (MSE) performance of empirical characteristic function (ECF) based signal level estimator in a binary communication system. By calculating Cramér-Rao lower bound (CRLB) we investigate the performance of the ECF based estimator in the presence of Laplace and Gaussian mixture noises. We have derived an analytic expression for the variance of the ECF based estimator which shows that it is asymptotically unbiased and consistent. Simulation and analytic results indicate that the ECF based level estimator outperforms the previously proposed estimators in some signal to noise ratio (SNR) regions when the observation noise distribution is unknown. 相似文献
12.
The power system state estimator based on the support vector machine (SVM) and the weighted least squares (WLS) method is presented in the paper. The WLS provides state estimations necessary for creating SVM model which is then used for state estimation. The developed algorithm was tested on the IEEE systems, and the performance indicators were calculated in order to compare the accuracy of estimation and the measurement error filtering. The results indicate that the proposed hybrid model outperforms the classical WLS-based state estimation in terms of accuracy and improves measurement error filtering in comparison to the classical estimator. 相似文献
13.
The Cramer–Rao lower bound (CRLB) that gives the minimal achievable variance/standard deviation for any unbiased estimator offers a useful tool for an assessment of the consistency of parameter estimation techniques. In this paper, a closed-form expression for the computation of the exact CRLB on unbiased estimates of the parameters of a two-dimensional (2-D) autoregressive moving average (ARMA) model with a nonsymmetric half-plane (NSHP) region of support is developed. The proposed formulation is mainly based on a matrix representation of 2-D real-valued discrete and homogeneous random field characterized by the NSHP ARMA model. Assuming that the random field is Gaussian, the covariance matrix of the NSHP ARMA random field is first expressed in terms of the model parameters. Then, using this matrix structure, a closed-form expression of the exact Fisher information matrix required for the CRLB computation of the NSHP ARMA model parameters is developed. Finally, the main formulas derived for the NSHP ARMA model are rearranged for its autoregressive and moving average counterparts, separately. Numerical simulations are included to demonstrate the behavior of the derived CRLB formulas. 相似文献
14.
Amal Helu 《Computational statistics & data analysis》2006,51(3):1523-1534
We estimate interclass (mom-sib) correlation by maximizing the log-likelihood function of a Kotz-type distribution. The results are illustrated on a real life data set due to Galton. Using extensive simulations and the three criteria, namely, bias, MSE and Pitman nearness probability, we compare the proposed estimator with the maximum likelihood estimator based on normal distribution and with a non-iterative estimator due to Srivastava. We conclude that the proposed estimator performs well when the data are not from multivariate normal distribution. However, if the data are from multivariate normal distribution then Srivastava's estimator and normal based maximum likelihood estimator perform well as expected. Testing of hypothesis about this correlation is also discussed using likelihood based tests. It is concluded that score test derived using Kotz-type density performs the best. 相似文献
15.
面目标跟踪系统状态估计问题中,附加的强非线性面目标扩展测量会增加系统的通信量和估计中心的计算量.为此,基于工程应用,提出一种不完全量测下的事件触发机制来控制面目标测量传输.从理论上推导了事件触发机制下面目标跟踪系统的理想(枚举)克拉美罗下界(Cramer-Rao lower bound,CRLB)和统计意义下的CRLB,该统计意义CRLB为理想CRLB的下界,计算复杂度远小于理想CRLB,便于工程应用.典型测试航路下的仿真结果表明:不完全量测下,面目标跟踪系统CRLB明显小于传统质点目标跟踪系统CRLB;同时,利用所提事件触发机制,可在大幅减少面目标跟踪系统通信量的同时保证系统的最优估计性能. 相似文献
16.
17.
18.
Performance evaluation of UKF-based nonlinear filtering 总被引:2,自引:0,他引:2
The performance of the modified unscented Kalman filter (UKF) for nonlinear stochastic discrete-time system with linear measurement equation is investigated. It is proved that under certain conditions, the estimation error of the UKF remains bounded. Furthermore, it is shown that the design of noise covariance matrix plays an important role in improving the stability of the algorithm. Error behavior of the UKF is then derived in terms of mean square error (MSE), and the Cramér-Rao lower bound (CRLB) is introduced as a performance measure. The modified UKF is found to approach the CRLB if the difference between the real noise covariance matrix and the selected one is small enough. These results are verified by using Monte Carlo simulations on two example systems. 相似文献
19.
无线传感器网络环境下受限于能量和带宽,传感器的观测往往需要经过量化后才发送,针对大规模不一致传感网络环境且带宽受限下的分布式状态估计,探讨了量化比特分配和估计性能评估问题。首先给出一种二进制概率量化方案,并基于量化观测构造线性无偏量化估计器。然后,考虑一个总的传输比特率限制下,得到了传感器的最优量化比特率及比特分配方案,由其信噪比(SNR)和总带宽确定。同时,对提出的量化估计器的均方误差上界进行了分析,发现其与理论下界仅相差一个小常数因子。最后,仿真结果表明,相比于一般的均匀比特分配,文中所提出的最优比特分配方案估计性能更优。 相似文献
20.
Analysis and performance evaluation of a pilot-aided interpolated channel estimator for OFDM systems
In this paper, we propose a novel pilot-aided channel estimator through interpolation for Orthogonal Frequency Division Multiplexing (OFDM) systems that replaces part of the virtual subcarriers with pilot subcarriers (pilots) reducing the interpolation error while keeping the code rate stable. A novel thorough analysis of the Mean Square Error (MSE) of the proposed estimator is given for the general case where data subcarriers are positioned before the first and after the last pilot. Simulations show the improvement of the proposed scheme in MSE and Bit Error Rate (BER) when applied to a practical OFDM wireless local area network type of system with realistic channel conditions. 相似文献