The transmitter of GEO-LEO system spaceborne bistatic radar located in geosynchronous orbit, and the receiver located in low orbit, which has the advantages of large beam coverage, anti-stealth and anti-interference, and has great application potential. However, the feature of large beam coverage requires the detection efficiency. For improving the detection efficiency, the best beam coverage area should be designed. In this paper, the detection area is divided by transmitting beam and receiving beam for simulating the real beam irradiation condition and the clutter suppression ability is used as the evaluation index to find the change rule of detection performance and the best detection position of the detection region. The simulation results show that the detection effect is best when the azimuth angle of the receiving beam is 90°, and the regional detection performance gradually becomes better with the extension of the detection distance.
This study focuses on the coherent integration (CI) of space-based distributed radar for space high-speed maneuvering targets. The platform space difference and high-speed motion result in the envelope position offset and phase difference of the inter-channel signals. Meanwhile, the high-speed and maneuvering characteristics of the target will lead to the range walk (RW) and doppler walk (DW) in the pulse accumulation in single node, which brings challenges to the detection of space targets. This paper presents a method for spatial-temporal joint coherent integration and parameter estimation based on the time-space range history. Firstly, based on the coupling relationship of spatial and temporal in the range history, we established inter-channel envelope correction and phase compensation function to address the inter-channel echo range and phase difference caused by spatial location differences between nodes. Secondly, we combined inter-channel synthetic compensation with generalized Radon-Fourier transform (GRFT). Thus, target range, angle, velocity, and acceleration parameter estimation are integrated into a unified framework. Finally, joint Spatial-temporal joint CI and parameter estimation for space-borne distributed radar system can be implemented. Simulation results demonstrate the effectiveness of the proposed method.
For the long-range and high-speed maneuvering space target detection, its performance is constrained by two challenges, the coherent integration loss due to Range migration and Doppler frequency spread, the contradiction between Range Ambiguity, and Doppler bandwidth ambiguity. This paper proposed a novel parameter estimation and integration method to solve the above two issues. Firstly, the waveform diversity technique is used to solve the range ambiguity problem. Then a matched filter bank for high-speed targets that can calculate the range ambiguity number is designed. Next, coherent integration is successfully achieved by estimating the target motion parameters and compensating for the echo signal. Finally, a two-step search strategy is proposed to improve the parameter estimation process, numerical experiments have validated that the complexity of the algorithm is reduced while ensuring the accuracy of the parameter estimation.
Space-borne bistatic radar has stronger viability than monostatic radar. And larger radar cross section (RCS) makes anti-stealth capability of space-borne bistatic radar stronger. However, space-borne bistatic radar is also in down-looking working state, which will suffer serious clutter interference. Since the transmitter and receiver are not placed on the same platforms, bistatic configurations cause clutter characteristics more complicated. It is mainly manifested in resolution spatial variation and tanglesome space-time distribution. In this paper, we first establish the signal model of spaceborne bistatic radar based on satellite-earth relation. Then, we focus on arbitrary orbital plane configuration to study resolution spatial variation and space-time distribution characteristics against bistatic geometric relationships. Last, we adopt the full link evaluation model to evaluate the performance of space-time adaptive processing (STAP) under corresponding bistatic geometric relationships. This paper can provide significant references for system design of space-borne bistatic radar.
Space-time adaptive processing (STAP) has been extended to the distributed space-borne multiple-input multiple-output (MIMO) radar system to improve the detection performance. Nevertheless, the transmitting waveforms are not completely orthogonal to each other, resulting in the STAP performance deterioration. In this paper, we established a novel STAP performance analysis model to reveal the influence mechanism of waveform properties. Firstly, the signal model of distributed space-borne radar with hybrid baseline and yaw angle was presented. Then, we derived the characteristic of the clutter covariance matrix for post-Doppler STAP, considering the effect of waveform periodic autocorrelation and cross-correlation sidelobe. Finally, the numerical simulation results, based on indicators of clutter eigenvalue spectrum and output signal-to-noise ratio loss, demonstrated the accuracy of the proposed analysis model. The aforementioned results provide important basis for the design of distributed space-borne MIMO radar system.
KEYWORDS: Signal processing, Signal to noise ratio, Feature extraction, Radar, Synthetic aperture radar, Signal detection, Radar signal processing, Filtering (signal processing), Time-frequency analysis
The fluent ship targets with micro-motion which is caused by oceanic waves leading to defocused images. Due to the large size ship, there is a multi-component echo signal in one range bin, thus it is crucial to extract the micro-Doppler (m-D) features quickly and precisely to refocus the images. This paper puts forward a novel micro-motion feature extraction and estimation method. The method is composed of two steps, and the first step is preprocessing to do the Short-Time Fourier Transform (STFT). After that, we propose a new form of synchrosqueezing transform to concentrate the energy spread curves which can be established as a state translation model. Then in the second step, we use the RFS-based Bernoulli filter to estimate the parameters of the multi-component signal. In this step, the method avoids the disturbance of stray points and empty areas so that the m-D parameters can be estimated accurately. The experimental results prove the availability of the proposed method and the accuracy of the estimation of m-D parameters.
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