In　order　to　enhance　the　anti-jamming　capability　of　aeronautic　swarm　tactical　network　in　the　complicated　electromagnetic　environment,　we　address　the　problem　of　bandit-based　cognitive　anti-jamming　strategy　for　enabling　reliable　information　transmission.　We　first　present　an　adversarial　multiuser　multi-armed　bandit　model　for　the　aeronautic　swarm　network　employing　airborne　cognitive　radios　with　the　same-frequency　simultaneous　transmit　and　receive　feature.　Then,　we　utilize　the　improved　energy　detection　method　to　perform　jamming　sensing　and　derive　the　closed　expression　of　false　alarm　probability,　false　detection　probability,　and　the　optimal　decision　threshold　in　the　case　of　single　and　multi-jammer　Finally,　using　the　jamming　sensing　output　to　calculate　reward　and　with　the　objective　of　maximizing　the　throughput　of　each　airborne　radio,　a　decentralized　selfish　doubling　trick　kl-UCB++　anti-jamming　strategy　is　developed　to　allocate　an　optimal　configuration　of　transmitting　power　and　spectrum　channel　to　each　radio.　This　anytime　bandit　strategy　is　simultaneously　minimaxed　optimal　and　asymptotically　optimal.　The　simulation　results　validate　that　the　aggregate　average　throughput,　cumulative　regret　obtained　with　the　proposed　anti-jamming　strategy　outperform　the　well-known　UCB,　kl-UCB++　bandit　algorithm.