# SMC-CPHD Filter with Adaptive Survival Probability for Multiple Frequency Tracking
## 2 Processing Steps of the SMC-CPHD Filter
In Proceedings of the 12 th International Conference on Information Fusion, Seattle, WA, USA, 6-9 July 2009; pp. 1171-1178. * [PERSON] and [PERSON] (2010) [PERSON]; [PERSON]; [PERSON] GMTI tracking via the Gaussian mixture cardinalized probability hypothesis density filter. _IEEE Trans. Aerosp. Electron. Syst._**2010**, _46_, 1821-1833. [CrossRef]
* [PERSON] et al. (2011) [PERSON]; [PERSON]; [PERSON]; [PERSON] A random-finite-set approach to Bayesian SLAM. _IEEE Trans. Robot._**2011**, _27_, 268-282. [CrossRef]
* [PERSON] (2018) [PERSON], [PERSON] Multiple frequency tracking method based on the cardinalised probability hypothesis density filter with cardinality compensation. In Proceedings of the 31 st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018), Miami, FL, USA, 24-28 September 2018; pp. 3504-3517. * [PERSON] et al. (2012) [PERSON]; [PERSON]; [PERSON]; [PERSON] Adaptive target birth intensity for PHD and CPHD filters. _IEEE Trans. Aerosp. Electron. Syst._**2012**, _48_, 1656-1668. [CrossRef]
* [PERSON] and [PERSON] (2015) [PERSON]; [PERSON] Refined GM-PHD tracker for tracking targets in possible subsequent missed detections. _Signal Process._**2015**, _116_, 112-126. [CrossRef]
* [PERSON] and [PERSON] (2018) [PERSON]; [PERSON]; [PERSON] PHD and CPHD Algorithms Based on a Novel Detection Probability Applied in an Active Sonar Tracking System. _Appl. Sci._**2018**, \(8\), 36. [CrossRef]
* [PERSON] and [PERSON] (2012) [PERSON] [PERSON]; [PERSON] State fusion with unknown correlation: Ellipsoidal intersection. _Automatica_**2012**, _48_, 1874-1878. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON] Decentralized data fusion with inverse covariance intersection. _Automatica_**2017**, _79_, 35-41. [CrossRef]
* [PERSON] et al. (2004) [PERSON]; [PERSON]; [PERSON] _Beyond the Kalman Filter: Particle Filters for Tracking Applications_; Artech House: London, UK, 2004. * [PERSON] et al. (2009) [PERSON]; [PERSON]; [PERSON] Gaussian mixture CPHD filter with gating technique. _Signal Process._**2009**, _89_, 1521-1530. [CrossRef]
* [PERSON] [PERSON] (2012) [PERSON]; [PERSON]. Adaptive gating for multitarget tracking with Gaussian mixture filters. _IEEE Trans. Signal Process._**2012**, _60_, 1533-1538. [CrossRef]
* [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON] Comparison of gating techniques for maneuvering target tracking in clutter. In Proceedings of the 17 th International Conference on Information Fusion, Salamanca, Spain, 7-10 July 2014; pp. 1-8. * [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON] Multi-target tracking using an improved Gaussian mixture CPHD Filter. _Sensors_**2016**, _16_, 1964. [CrossRef] [PubMed]
* [PERSON] and [PERSON] (2006) [PERSON]; [PERSON] Convergence results for the particle PHD filter. IEEE Trans. _Signal Process._**2006**, _54_, 2652-2661. * [PERSON] et al. (2006) [PERSON]; [PERSON]; [PERSON]; [PERSON] Convergence of the SMC Implementation of the PHD Elite. _Methodol. Comput. Appl. Probab._**2006**, \(8\), 265-291. [CrossRef]
* [PERSON] and [PERSON] (2017) [PERSON]; [PERSON]. Practical method to predict an upper bound for minimum variance track-to-track fusion. _IET Signal Process._**2017**, _11_, 961-968. [CrossRef]
* [PERSON] (2002) [PERSON] Information fusion based on fast covariance intersection filtering. In Proceedings of the 5 th International Conference on Information Fusion, Annapolis, MD, USA, 8-11 July 2002; pp. 901-904. * [PERSON] et al. (2012) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Sequential covariance intersection fusion Kalman filter. _Inf. Sci._**2012**, _189_, 293-309. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A survey on multisensor fusion and consensus filtering for sensor networks. _Discret. Dyn. Nat. Soc._**2015**, _2015_, 683701. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] Cardinality compensation method based on information-weighted consensus filter using data clustering for multi-target tracking. _Chin.