The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对单跳质心算法进行多跳扩展以改善定位比率，并加入场强加权过程和去中心化过程以提高定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权质心法是一种较为理想的细分定位方法，不仅简单、易于实现，而且具有更高的定位精度以及抗噪声的能力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该法对单跳法进行多跳扩展以改善定位比率，并加入场强加权过程和去中化过程以提高定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权法是一种较为理想的细分定位方法，不仅简单、易于实现，而且具有更高的定位精度以及的能力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对单跳质心算法进行多跳扩展以改善定，并加入场强加权过程和去中心化过程以提高定精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权质心法是一种较为理想的细分定方法，不仅简单、易于实，具有更高的定精度以及抗噪声的能力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对单跳质心算法进行多跳扩展以改善定位比率，并加入场强加权和去中心以提高定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通实验表，平方加权质心法是一种较为细分定位方法，不仅简单、易于实现，而且具有更高定位精度以及抗噪声能力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对跳质心算法进行多跳扩展以改善定位比率，并加加权过程和去中心化过程以提高定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权质心法是一种较为理想的细分定位方法，不仅、于实现，而且具有更高的定位精度以及抗噪声的能力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对心算法进行多扩展以改善定位比率，并加入场强加权过程和去中心化过程以提高定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权心法是一种较为理想细分定位方法，不仅简、易于实现，而且具有更高定位精度以及抗噪力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对单质心算法进行展以改善比率，并加入场强加权过程和去中心化过程以提高度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权质心法是一种较为理想的细分方法，不仅简单、易于实现，而且具有更高的度以及抗噪声的能力。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对单跳质心算法进行多跳扩展以改善定位比率，并加入场强加权过程和去中心化过程以提高定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权质心法是一种较为理想的细定位方法，不仅简单、易于实现，而且具有更高的定位精度以及抗噪声的能。

The proposed algorithm improves localized nodes ratio by multihop centroid calculating，and improves localization accuracy by decentralizing process and signal strength-weighting process.

该算法对单跳质心算法进行多跳扩善定位比率，并加入场强加权过程和去中心化过程提定位精度。

Finally experiments indicate that squared cancroid method is better, which is simple and easy implemented and improves the locating precision and the Noise resisting ability.

通过实验表，平方加权质心法是一种较为理想细分定位方法，不仅简单、易于实现，而且具有定位精度及抗噪声能力。