Underwater Passive Acoustic Target Location Based On Doppler Frequency Shift

Underwater passive acoustic target localization is a localization method in which the sensor passively receives the acoustic signal emitted by the underwater target and estimates the moving parameters of the target through the acquired acoustic signal information.This positioning method is widely used for underwater robot positioning and navigation,beacon positioning and so on,so underwater passive acoustic target positioning has important research significance and application value.Underwater passive acoustic target positioning has the characteristics of long detection distance,low power consumption and strong anti-interference ability.In addition to the problems of energy consumption,environmental noise and narrow bandwidth of data transmission,there are propagation delays in the propagation of acoustic signals.When there is relative motion between the underwater acoustic target and the sensor,the sensor can measure the change of the frequency of the acoustic signal emitted by the target,that is,the Doppler shift.Compared with wireless RF signals,the underwater acoustic propagation speed is lower,and simply ignoring its propagation delay often leads to large errors in positioning.This paper considers the use of Doppler shift to solve the problem of underwater passive target location.Use Doppler measurements to improve target positioning accuracy.This paper aims at the above problems to carry out the following work:1.Aiming at positioning problem based on Doppler shift measurement,we introduce various localization algorithms,including the classical maximum likelihood(ML)algorithm,least squares estimation(LSE)algorithm,weighted least squares(WLS)algorithm,and the Cramér-Rao lower bound(CRLB).Computer simulations are performed to illustrate the performance of those algorithms.The results show that the root mean square error curve of the ML algorithm is closer to CRLB.The WLS algorithm outperforms the LSE algorithm.2.Aiming at the positioning problem under the constraints of acoustic signal propagation delay,a Doppler frequency shift measurement model considering time delay compensation is established,and an ML localization algorithm with time delay constraints is proposed.Taking advantage of the log-likelihood function after considering the delay,the new CRLB is derived as a benchmark for performance comparison of different positioning algorithms.The simulation results show that with the increase of the speed of the sensor or the distance between the sensor and the target,the effect of the time delay on the accuracy of target location is greater.3.A two-step Closed-Form(TSCF)localization algorithm with delay constraints is proposed to solve the problem of maximum likelihood optimization without closed solutions.Firstly,the target position is estimated using the current sensor position.Secondly,the delay time of acoustic signal is obtained by using the distance between the current sensor position and the estimated target position,and then the sensor position after delay compensation is obtained,and the estimated target position is updated.The simulation results show that under the condition of large measurement noise,the TSCF algorithm is close to the closed algorithm without considering delay.However,its performance is significantly improved when the measurement noise is small.