To solve the mismatch problems between the measurement likelihood function, importance density function and the target true distribution for the nonlinear filtering in the presence of the model attribute ambiguity and prediction bias, we derive and present a Bayesian sequential importance quadrature filter(SIQF) algorithm. To reduce the deviation between the likelihood function and the target true distribution in the Bayesian reference, the bounded measurement likelihood of the latest measurement is defined via the soft spatiotemporal constraint, the modified prior of the feasible area is approximated by truncating the probability density function of the measurement noise. To modulate the matching degree between the importance function and the target distribution, the state under the modified and original priors is evaluated via Gauss-Hermite Kalman filter in parallel, the maximum correntropy criterion is introduced to construct the mixture importance function, both the diversity of sequential importance sample and the tolerance of prediction covariance can be thereby improved. The simulation results show that, compared with the unscented particle filter for the estimation of one-dimensional univariate nonstationary growth model, the average estimate error of the SIQF algorithm has decreased 63% without sacrificing computational complexity. Compared with the multi-model Rao-blackwell particle filter for the maneuvering target tracking in the airspace, the root mean square error of the SIQF algorithm has decreased 33%, and the computational load is reduced by an order of magnitude.

Pseudolites have the ability to transmit the same signals as GNSS(Global Navigation Satellite System) satellites, and can provide stable and reliable positioning signals for the navigation signal obstructed environment, making it possible to achieve continuous high-precision positioning outdoors based on the existing terminal hardware conditions. Therefore, it has gradually become a research hotspot in the field of indoor positioning. In this paper, a fingerprint database matching and positioning method based on homologous multi-channel pseudolites is proposed. The variational autoencoder network that takes into account the position information is designed to learn the probability distribution characteristics of the pseudolite carrier phase information in the hidden space. Then, the mapping relationship between the hidden features of the pseudolite observation data and the indoor location is established. After this, aiming at the problem of large fluctuation of fingerprint location results, a particle filter fusion processing method is proposed to improve the stability and accuracy of the location system. In the experimental environment and airport environment, a large number of experiments verify the positioning performance of the positioning algorithm under dynamic and static conditions, and compare it with the common positioning methods based on fingerprint database matching. The results show that the dynamic average positioning accuracy is 0.39 m in the indoor test environment, and 95% of the positioning error is better than 0.85 m. In the real airport environment, the dynamic average positioning accuracy is 0.75 m, the maximum positioning error is 1.69 m, and 92% of the positioning error is better than 1m. The effectiveness of the algorithm is verified.

Currently, global navigation satellite systems(GNSS) can provide stable and reliable positioning services in open environments. However, due to the occlusion and attenuation of satellite signals, there is still challenges of high accuracy positioning in weak signal environments. Pedestrian dead reckoning(PDR) is an effective complementary solution for positioning, but it needs an initial heading angle and faces the critical problem of error accumulation. The digital terrestrial multimedia broadcasting(DTMB) signals have strong transmission power, which contributes to better urban propagation and building penetration, and the signal transmitters are well placed in the city, so it has great potential in terms of positioning. To this end, this paper proposed a PDR motion parameter correction method constrained by the single base station DTMB signals. In our study, a complete DTMB signal receiver based on software radio is developed, and the wireless ranging method based on DTMB signal is studied. The constraint function of the initial heading angle is constructed by wireless distance, and the initial heading angle of PDR can be corrected by solving the function. To reduce the accumulated errors during the pedestrian motion, the PDR motion parameters are fused with the wireless distance through particle filtering to obtain the corrected positioning results for pedestrians. The results of the field test in Wuhan, China, showed that the positioning errors of the proposed method can effectively position in both DTMB signal intervisibility scene and incomplete intervisibility scene. Compared with PDR, the 95% positioning error is reduced by 41% and 30% respectively, which verifies the feasibility and effectiveness of the proposed method.

The radio local positioning system(RLPS) requires a spatial reference autonomous establishment technology with high-precision, high-efficiency, and high-robustness. A distributed spatial reference autonomous establishment technology is proposed based on the alternating coordinate descent(ACD) method. By associating the local optimization of a node with the global optimization of the system, the coordinate descent method is used to achieve distributed high-precision positioning. We analyzed the algorithm convergence and proposed a parallel optimization strategy by searching independent sets of network topology. The ranging information is deeply integrated with the anchor information in the optimization model to obtain absolute coordinates of nodes. Simulation and experimental results show that the proposed distributed algorithm can effectively shorten the positioning time while obtaining high-precision positioning results.

Generalized frequency division multiplexing(GFDM) is a novel multi-carrier modulation technology with the characteristics of subcarrier non-orthogonality and flexibility of time-frequency resources. GFDM is expected to become a new waveform design of mobile communication technology in the beyond fifth-generation(B5G) or sixth-generation(6G) era. This paper proposes a high-precision carrier ranging method based on GFDM signal, which mainly includes steps of coarse synchronization, pilot detection, multipath extraction, first path acquisition, delay tracking and carrier phase ranging. To verify the above-mentioned method, we built an experimental platform in typical indoor meeting scenarios. Test results showed that using GFDM signals the probability of ranging accuracy within 1.1 m is 95%, which is 21% better than the ranging performance of OFDM signals with the same bandwidth. In addition, the positioning error interval of GFDM is within 2 m. The research in this paper provides a useful reference for next-generation mobile communication indoor positioning technology.

Timing is one of the basic services of GNSS(Global Navigation Satellite System) and plays an important role in advanced electronic equipment developing and intelligent spatiotemporal information service. Current GNSS timing methods are limited to common-view station and communication network. To deal with these problems, we propose a precise point timing method based on BDS-3(BeiDou Navigation Satellite System) B2b signal, called B2b-PPT(B2b signal based Precise Point Timing), which using dual frequency observations and estimating receiver clock by precise point positioning algorithm. After UTC(Universal Time Coordinated) bias correction and hardware delay calibration, the B2b-PPT receiver disciplines the clock to realize precise time-frequency synchronization. Experimental results based on iGMAS(international GNSS Monitoring and Assessment System) stations show that the accuracy of timing using B2b-PPT method is 0.58 ns and the frequency stability at 10 hours is 6.9E-15 in single station mode, corresponding indicators are 0.33 ns and 1.1E-14 respectively in station difference mode. In conclusion, the performance of B2b-PPT method is better than traditional GNSS precise point timing method, and the B2b-PPT method also has the advantage of low cost and being independent of ground communication network and analysis center.