Track-before-detect (TBD) in range-Doppler plane is of significance for Doppler radars. The existing methods suffer from the approximate motion models in range-Doppler plane and the inefficiency of energy integration. In this paper, an accurate evolution equation of target range and Doppler with respect to time is presented and a new pseudo-spectrum based TBD method is proposed to effectively integrate target energy and detect weak target in range-Doppler domain. According to the commonly assumed constant velocity motion in Cartesian coordinates, the evolution of range and Doppler is correctly described by a nonlinear function of target range-Doppler and the time invariant speed square. Consequently, a novel TBD method, which matches target speed instead of velocity in each direction, is proposed. Each original resolution cell in range-Doppler plane is predicted to the last frame of current processing batch according to the time evolution equation. Then, a pseudo-spectrum is constructed around the predicted position according to a point spread function. Multiframe accumulation is achieved by adding the sampling values of the pseudo-spectrum over several cells to the last frame. To match the unknown target speed square, a bank of pseudo-spectrum based speed square filter (PS-SSF) is presented. The target output envelopes in both range-Doppler and speed square domains are derived theoretically and a feasible parameter estimation method is proposed. Numerical simulation results demonstrate that the proposed PS-SSF method can not only achieve effective weak target detection in range-Doppler domain, but also produce precise parameter estimates of target range and Doppler, as well as target speed.

Conventional velocity-filtering-based track-beforedetect (VF-TBD) methods integrate the energy of a cell in a frame with that of the cell closest to the predicted target position in the last frame of the processing batch, assuming a certain target velocity. However, the target may not exactly be on the quantized cell and its echo envelope may occupy multiple adjacent cells. This often leads to significant energy loss and echo envelope degradation. In this paper, a novel VF-TBD method based on pseudo-spectrum (PS-VF-TBD) is presented to address this problem. For every cell, a pseudo-spectrum is constructed around the predicted position according to the assumed velocity using a truncated point spread function. Samples of the pseudospectrum on the cells that are located in the truncated spread area are added onto the last frame of the processing batch to integrate the target energy within multiple cells. Due to the use of the point spread model and the accurate sampling of the predicted spectrum, energy loss can be mitigated and the echo envelope well maintained. This approach simultaneously maximizes the signal-to-noise ratio (SNR) gain and enables improved parameter estimation utilizing the envelope characteristics. The procedure for pseudo-spectrum construction and multi-frame accumulation is derived in detail and the output SNR is analyzed theoretically. It is found that the proposed PS-VF-TBD can achieve an SNR gain greater than that by the conventional VF-TBD method. To deal with a target with unknown velocity, a bank of pseudospectrum- based velocity filters is proposed. The signal gain loss resulting from velocity mismatch is investigated and the μ-width of the envelope in the velocity domain is analyzed. Finally, a method for improved position and velocity estimation is presented. Simulation results demonstrate the superiority of the proposed method in terms of SNR gain, detection probability and estimation accuracy at the expense of increased computational complexity

Track-before-detect (TBD) of weak maneuvering targets in range-Doppler plane is investigated. The existing TBD methods suffer from performance degradation due to the use of approximate motion models in range-Doppler plane. In this paper, exact time evolving rules of target range and Doppler are presented for constant acceleration (CA) and coordinated turn (CT) motions in Cartesian coordinates, and two novel pseudo-spectrum based TBD approaches are proposed for effective detection of weak CA and CT targets in range-Doppler plane, respectively. In accordance with the common CA and CT motions in Cartesian coordinates, the accurate time evolution equations of range and Doppler are derived for CA and CT targets, respectively, which are nonlinear functions of range-Doppler and several invariable parameters. Then, the pseudo-spectrum based TBD of CA and CT targets in range-Doppler plane is performed by matching these invariants. Each range-Doppler cell is predicted according to the exact evolution equation. A pseudo-spectrum is constructed around the predicted position, and sample values of the pseudo-spectrum are added onto cells for energy integration. This eliminates performance loss caused by model mismatch and target output envelope can be well maintained. To deal with the unknown target parameters, two pseudo-spectrum based matched filter banks are proposed for CA and CT targets, respectively. Analysis and design of the filter banks are provided in detail. Simulations are conducted to evaluate the validity of the proposed methods in handling weak maneuvering targets.

Traffic-related particulate matter (PM) is one of the major sources of air pollution in metropolitan areas. This study is to observe the interactive effects of gene and fine particles (particles smaller than 2.5 μm - PM2.5) on the respiratory system and explore the mechanisms linking PM2.5 and pulmonary injury. The participants include 110 traffic policemen and 101 common populations in Shanghai, China. Continuous 24 h individual-level PM2.5 is detected and the pulmonary function, high-sensitivity C-reactive protein (hs-CRP), Clara cell protein 16 (CC16) and the polymorphism in CXCL3, NME7 and C5 genes are determined. The multiple linear regression method is used to analyze the association between PM2.5 and health effects. Meanwhile, the interactive effects of gene and PM2.5 on lung function are analyzed. The individual PM2.5 exposure for traffic policemen was higher than that in the common population whereas the forced expiratory volume in 1 s (FEV1), the ratio of FEV1 to forced vital capacity (FEV1/FVC) and lymphocytes are lower. In contrast, the hs-CRP level is higher. In the adjusted analysis, PM2.5 exposure was associated with the decrease in lymphocytes and the increase in hs-CRP. The allele frequencies for NME7 and C5 have significant differences between FEV1/FVC ≤ 70% and FEV1/FVC > 70% participants. The results didn't find the interaction effects of gene and PM2.5 on FEV1/FVC in all the 3 genes. The results indicated that traffic exposure to high levels of PM2.5 was associated with systemic inflammatory response and respiratory injury. Traffic policemen represent a high risk group suffering from the respiratory injury.

In this paper, a velocity filtering based track-before-detect algorithm in mixed coordinates is presented to address the problem of integration loss caused by inaccurate motion model in polar coordinate sensors. Since the motion of a constant velocity (CV) target is better modeled in Cartesian coordinates, the search of measurements for integration in polar sensor coordinates is carried out according to the CV model in Cartesian coordinates instead of an approximate model in polar sensor coordinates. The position of each cell is converted into Cartesian coordinates and predicted according to an assumed velocity. Then, the predicted Cartesian position is converted back to polar sensor coordinates for multiframe accumulation. The use of the correct model improves integration effectiveness and consequently improves algorithm performance. To handle the weak target with unknown velocity, a velocity filter bank in mixed coordinates is presented. The influence of velocity mismatch on the performance of filter bank is analyzed, and an efficient strategy for filter bank design is proposed. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm.