Conflict of interest

The authors declare no conflict of interest.

Robust Guidance Algorithm against Hypersonic Targets DOI: http://dx.doi.org/10.5772/intechopen.84655

4. Conclusions

Military Engineering

NPDG.

accuracy and robustness to guidance noises.

The authors declare no conflict of interest.

Acknowledgements

and 2019TC108).

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Conflict of interest

This chapter first discusses how to solve the problem of intercepting the hypersonic maneuvering target without greatly increasing the complexity degree of the guidance system. Based on the axiom that the response to the target maneuver of the differential signal of the line-of-sight rate is faster than that of the line-of-sight rate, a nonlinear proportional and differential guidance law is designed using the differential derivative of the line-of-sight rate. Based on the differential definition of fractional calculus, a fractional calculus guidance law is designed on the basis of the NPDG. In the simulation experiments of interception accuracy and robustness, both the NPDG and the FCG demonstrate guaranteed guidance performances. The influence of noises impacting on the guidance system is studied. Both of the guidance laws can effectively intercept hypersonic maneuvering targets while reducing the impact of noise signals. Furthermore, the method obtaining the fractional differential signal of q\_ in the FCG is better than the method estimating the q€ in the

In conclusion, under the premise of not greatly increasing the complexity degree of the guidance system, introducing the differential signal of the line-of-sight rate to formulate the novel guidance laws can help meet the precision needed to intercept a hypersonic weapon. The FCG is superior to the NPDG in interception

This work is supported by National Key R&D Program of China (Grant Nos. 2016YFC0400207, 2017YFD0701003 from 2017YFD0701000, and 2016YFD0200702 from 2016YFD0200700), the Jilin Province Key R&D Plan Project 2017YFD0701000, and 2016YFD0200702 from 2016YFD0200700), the Jilin (Grant Nos. 20180201036SF and 20170204008SF), and the Chinese

Universities Scientific Fund (Grant Nos. 10710301, 1071-31051012, 1071-31051361,
