There are two methods either by Probabilistic Methods or Deterministic method.
Deterministic Methods works well when length of the unknown vector becomes very large .
For probabilistic Method you generate a matrix randomly and then normalize it.
There are several works in this area. I specially recommend you the work of professor Tran. I attach a related paper: http://thanglong.ece.jhu.edu/Tran/Pub/SRM_TSP.pdf
http://thanglong.ece.jhu.edu/Tran/Pub/SRM_TSP.pdf
For the measurement matrix with low coherence I suggest you to view this papers :
Talwalkar, A., & Rostamizadeh, A. (2010). Matrix coherence and the nystrom method. arXiv preprint arXiv:1004.2008.
Baraniuk, R. G. (2007). Compressive sensing. IEEE signal processing magazine, 24(4).
Tropp, J. A., & Gilbert, A. C. (2007). Signal recovery from random measurements via orthogonal matching pursuit. Information Theory, IEEE Transactions on, 53(12), 4655-4666.
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