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Landing footprint is critical to generate a feasible trajectory onboard for entry vehicles. In this paper, a new landing footprint calculation based on geometry-predicted trajectory is proposed. First, the lateral motion states, turning radius and angle, are analytically solved based on a planned drag acceleration vs. energy (D–E) profile. Through some simple coordinate and geometrical triangle transformation, all the trajectory states are extracted. Second, by calculating the maximum longitudinal range point, the furthest reachable boundary for planned D–E profile is obtained with proposed geometry-predicted trajectory. Finally, the landing footprint can be generated by repeatedly computing the reachable boundaries for all D–E profiles in the entry corridor. Simulation results with Common Aero Vehicle (CAV) model validate the accuracy of the geometry-predicted trajectory. Furthermore, detailed comparison of footprint generation results between the traditional and the proposed are presented at last. [ABSTRACT FROM AUTHOR]

During June and July 2003, CO, NO2, THC and PM10 were sampled at the four highway toll gates in Chongqing. Air temperature, air pressure, wind velocity and traffic flow were also monitored simultaneously. The relation between air pollution parameters and influencing factors was analyzed by applying the methods of bivariate correlation and partial correlation. As shown in the monitoring result, the outdoor average concentrations of CO and PM10 exceed indoor ones, but NO2 and THC are reverse. The average concentrations of CO and NO2 at the toll gates don't exceed the indoor and outdoor air quality standards except for the toll gate in Chongqing and Chayuan. One-hour average concentrations of outdoor and indoor THC are 7.728 mg/m3 and 7.216 mg/m3 respectively, and exceed ten times of the indoor air quality standard. One-hour average concentrations of indoor and outdoor PM10 change acutely respectively, and the their maximum concentrations are 0.631 mg/m3 and 0.217 mg/m3 which exceed indoor air quality standard and the second class of ambient air quality standard. Polluting state of Chongqing toll is the worst among the four sampled tolls, and three indexes are bigger than others. Indoor and outdoor air pollutants have correlativity. Correlations of CO, PM10 and NO2 are significant at the 0.01 level respectively, and correlations between indoor and outdoor THC are significant at the 0.05 level. In the influencing factors analysis, traffic flow is significantly correlative with NO2, THC and PM10 (p < 0.01 or 0.01 < p < 0.05), and not significantly correlative with CO (p > 0.01). Air pressure and ambient temperature are predominating factors which influencing the concentration variation, and wind speed is a minor meteorological factor influencing the fluctuations of the data.