A two-level Nested array is employed to construct a sparse L-shaped array. For this array, an angle estimation method based on compressed sensing is proposed. This method calculates the autocorrelation covariance matrix of the received data and quantizes it, and then reorders and removes the redundancy to obtain the incidence angle information of the virtual array. The length of the virtual array is much larger than that of the actual physical array, so compared with the uniform L-shaped array with the same physical array element, the array aperture and degree of freedom have been greatly improved. Finally, the orthogonal matching pursuit technique is adopted to solve the l₁ norm constraint problem of the virtual array. Computer simulation shows that the proposed algorithm has higher source resolution and better estimation performance under the conditions of high signal-to-noise ratio, high snapshot number and large angle interval.