It implemented an SDP based approach with regularization for solving sensor network localization problems. The algorithm first solves an SDP relaxation (with regularization) of the non-convex minimization problem (1), and use the SDP computed solution as the starting point for a gradient descent method with backtracking line search to solve the smooth unconstrained problem (2).

This software package is designed for solving small size senor network localization problems with up to 200 sensors and a few thousands given distances.

\( (1)\quad \min \big\{ \sum_{(i,j)\in {\cal E}} | \|x_i-x_j\|^2-d_{ij}^2| + \sum_{(k,j)\in {\cal F}} | \|a_k-x_j\|^2-d_{kj}^2 | \big\} \\[10pt] (2)\quad \min \big\{ \sum_{(i,j)\in {\cal E}} ( \|x_i-x_j\|-d_{ij})^2 + \sum_{(k,j)\in {\cal F}} (\|a_k-x_j\|-d_{kj})^2 \big\} \)

where \(d_{ij}, d_{kj} \) are distance data, \(x_j\) is the position of the jth sensor, and \(a_k\) is the position of the kth anchor.If you find SNLSDP useful in your work, please cite the following paper:

[1] P. Biswas, T.-C. Liang, K.-C. Toh, T.-C. Wang, and Y. Ye, Semidefinite programming approaches for sensor network localization with noisy distance measurements, IEEE Transactions on Automation Science and Engineering, 3 (2006), pp. 360--371.

- Copyright: This version of SNLSDP is distributed under the GNU General Public License 2.0. For commercial applications that may be incompatible with this license, please contact the authors to discuss alternatives.
**Download SNLSDP-0.zip**

Please read. Welcome to SNLSDP-0! The software requires a few Mex files for execution. You can generate (only need to be done once) these executable files as follows:- Firstly, unpack the software:

unzip SNLSDP-0.zip - Run Matlab in the directory SNLSDP-0
- In the Matlab command window, type:

>> cd SDPT3-4.0

>> Installmex

>> cd .. - After that, to see whether you have installed SNLSDP correctly,
type:

>> startup

>> testSNLsolver - By now, SNLSDP is ready for you to use.

- Firstly, unpack the software: