Research On Low-Complexity Angle Estimation Method For Bistatic MIMO Radar

Colocated multiple-input multiple-output(MIMO)radar effectively reduces the radar interception probability and improves the target detection and parameter estimation capabilities by generating high-width,low-gain signal beams at the transmitter using orthogonal waveform transmission technology.For bistatic radar,the separated transmit and receive antennas can effectively avoid exposure to electromagnetic interference sources,enhance the radar’s stealth and ability to counter stealth targets,enabling the radar system to better adapt to complex combat environments.The bistatic MIMO radar system studied in this paper combines the unique potential of the bistatic system with the fundamental advantages of MIMO radar,compensating for certain shortcomings of each.Therefore,in military and civilian fields,bistatic MIMO radar has broad application prospects and significant importance.The virtual array formed by the bistatic MIMO radar can increase the aperture of the antennas,thereby obtaining spatial gain.It can improve the reliability of radar detecting targets and the accuracy of target parameter estimation.However,this method significantly increases system complexity and hardware cost.This paper focuses on the high complexity of the bistatic MIMO radar and proposes solutions to reduce system complexity and hardware cost from the perspectives of compressed array structure and mixed-resolution analog-todigital converters(ADCs)quantization.The main work and contributions are as follows:1.The received signal model of the bistatic MIMO radar under narrowband signal conditions is analyzed,and the working principle and received signal processing methods of the bistatic MIMO radar are systematically studied.Since the echo signals of the bistatic MIMO radar contains the target’s spatial position information,that is,the information of the direction of departure(DOD)relative to the transmitting array and direction of arrival(DOA)relative to the receiving array.By processing the echo signals,joint estimation of the target’s DOD and DOA can be obtained.Therefore,this paper focuses on the analysis of two fundamental methods for joint DOD and DOA estimation,namely the two-dimensional multiple signal classification(MUSIC)algorithm and the reduced-dimension MUSIC estimation algorithm.2.In general,the DOD and DOA parameters can be estimated through two-dimensional or reduced-dimensional search algorithms,but the estimation performance depends on the equivalent array aperture,which requires a large number of antennas to achieve higher estimation performance,resulting in significant increases in system costs and computational complexity.Therefore,this paper proposes the compressive bistatic MIMO radar,where the compressive sampling is separately performed in each receive antenna.Additionally,the tensor model of proposed structure is constructed.To fully exploit the structure of the bistatic MIMO radar,we propose a joint DOD and DOA estimation algorithm based on high-order singular value decomposition(HOSVD).However,HOSVD separates DOA and DOD into two independent dimensions,which produces cross-terms.Therefore,this paper introduces a pairing algorithm that eliminates cross-terms by utilizing the relationship between the covariance matrix and the covariance tensor,in order to achieve joint angle estimation.In addition,the Cramér-Rao bound(CRB)is derived for the compressive bistatic MIMO radar and the computational complexity is analyzed from the perspective of the receive dimension.Simulation results show that the proposed scheme outperforms the conventional MIMO radar,and the proposed tensor-based algorithm has a better estimation performance than the matrixbased MUSIC.3.MIMO radar faces two major challenges: high hardware costs and power consumption.The use of low-resolution ADCs is considered a promising approach to address these issues.However,simple quantization with low-resolution ADCs can lead to performance loss.To balance performance loss,circuit costs,and energy consumption,mixed-resolution ADCs structures are first studied in a uniform linear array and the corresponding CRB expressions for multiple sources are derived to verify the performance differences among different mixedresolution ADCs structures.Then,this paper applies mixed-resolution ADCs to the bistatic MIMO radar,derives the corresponding CRB expressions for multiple sources,and verifies its performance through simulation results.The simulation results show that mixed resolution quantization structures can balance performance loss,circuit costs,and power consumption well.Moreover,the estimation performance varies among different quantization structures with the same number of quantization channels.