The authors experimentally demonstrate that the spectral flatness of chaotic light from an external-cavity feedback semiconductor laser is significantly improved using a fibre Bragg grating. The effects of detuning between the Bragg frequency and chaotic frequency on the bandwidth and spectral flatness are both investigated. The flatness of the power spectrum is enhanced to ±1.4 dB whilst maintaining the spectral bandwidth at around 8 GHz. The experimental results are in accordance with theoretical predictions which also have shown that the spectral flatness decreases initially then increases with increasing the 3 dB bandwidth of grating. A flattened spectrum with a low-pass energy distribution increases the utilisation efficiency of chaotic light in chaotic radar and reflectometry.

LMS algorithm is a kind of classic adaptive algorithms. Although it has the virtue of simple operation, it also shows the defects of relatively slow convergence and big steady state errors in low SNR. To remedy these defects, this paper put forward a new variable steps adaptive LMS algorithm. In the transient state, the learning rate increases slowly with the iteration times which accelerate the convergence rate of LMS algorithm. In the steady state, the learning rate decreases gradually with the iteration times which guarantee the convergence accuracy of LMS algorithm. After this improved algorithm is applied in the design of adaptive wavetrap, the simulation results show that it can not only effectively ease up the conflicts between convergence rates and steady state errors, but also improve the performance of wavetrap in real-time trapping.