A Fast Range Ambiguity Resolution Method for Short-Period Direct-Sequence Spread Signals in Radar Measurement

Abstract

This invention discloses a method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals used in radar measurement. The method comprises: 1) designing a square wave period based on the maximum unambiguous measurement range requirement; 2) transmitting a direct-sequence spread spectrum signal modulated with a square wave at the transmitting end; 3) estimating the code phase within the spread spectrum pseudocode period at the receiving end using fast circular correlation; and 4) despreading using the spread spectrum pseudocode phase estimation result and accumulating energy within the spread spectrum pseudocode period to obtain N. s The energy accumulation results are as follows: 5. The energy accumulation results within adjacent spread spectrum pseudocode periods are used to search for the square wave transition edge using a differential method to complete target detection decision and distance estimation; This invention can effectively improve the maximum unambiguous distance for capturing high dynamic weak signals, while resolving the contradiction between computing resources and acquisition time.

Description

Technical Field

[0001] This invention belongs to the field of radar detection technology, specifically relating to a fast range ambiguity resolution method based on square wave modulated short-period direct sequence spread spectrum signal for radar measurement. Background Technology

[0002] Direct sequence spread spectrum (DSS) signals possess excellent anti-jamming, anti-multipath, and anti-interception performance, as well as high measurement accuracy, making them widely used in radar measurement and control. The period of the DSS signal directly determines the maximum unambiguous range that the radar can measure, which can typically be extended by increasing the pseudocode length or symbol width. However, increasing the pseudocode period directly leads to a longer acquisition time for the DSS signal. Parallel acquisition algorithms can effectively shorten the acquisition time, but the hardware resources consumed by implementing these algorithms increase dramatically.

[0003] To address the range ambiguity problem in direct sequence spread spectrum signals, the 1999 publication "Radio Communication Technology" proposed...

[0004] In his paper "Resolving Range Ambiguity in Continuous Wave Pseudocode Ranging Radar" (pages 16-19 of issue 6), Wang Bin proposed a method for range ambiguity resolution by changing the code clock. This method increases the radar's effective range while maintaining the original ranging accuracy and acquisition time. However, the algorithm requires the difference between two measurements to be measured at the same time. Since the system dictates that these two values ​​need to be measured separately, the acquisition speed after the code clock conversion is very important; otherwise, it will cause a large range error. In 2012, Xie Chao from Changchun University of Technology used JPL (Jet Propulsion Laboratory) fast acquisition codes generated based on mm composite sequences as the ranging codes of the system in his master's thesis "Research on Wireless Ranging Method Based on PN Sequence" to effectively improve the maximum unambiguous range. However, the method of generating composite codes is relatively complex and not conducive to hardware implementation.

[0005] Therefore, existing technologies suffer from problems such as high computational resource consumption, high complexity, and high requirements for capture speed. Summary of the Invention

[0006] In view of this, the present invention provides a method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals for measuring radar, which can effectively improve the maximum unambiguous range for capturing high-dynamic weak signals, while resolving the contradiction between computing resources and acquisition time.

[0007] The technical solution for implementing the present invention is as follows:

[0008] A method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals for radar measurement includes the following steps:

[0009] Step 1: Design the square wave period based on the maximum unambiguous measurement distance requirement;

[0010] Step 2: The transmitting end transmits a direct sequence spread spectrum signal with square wave modulation;

[0011] Step 3: The receiver estimates the phase of the spread spectrum pseudocode within the period using fast circular correlation.

[0012] Step 4: Despread using the phase estimation result of the spreading pseudocode, and accumulate energy within the spreading pseudocode period to obtain N. s The result of energy accumulation;

[0013] Step 5: The energy accumulation results within adjacent spread spectrum pseudocode periods are used to search for the square wave transition edge using a differential method to complete the target detection decision and distance estimation.

[0014] Furthermore, based on the maximum unambiguous measurement distance requirement of Rkm, the square wave period should not be less than [a certain value]. Where c is the speed of light; for ease of engineering purposes, T ms is considered as the period of the positive and negative square waves. The square wave period is 2Tms, and the maximum unambiguous measurement distance can reach 150T km.

[0015] Furthermore, at the transmitting end, the modulated data is first multiplied by the pseudo-code to complete the spread spectrum, then multiplied by the square wave to increase the maximum unambiguous distance, and finally modulated to the intermediate frequency f. I This generates a transmission signal.

[0016] Furthermore, for N after energy accumulation s The square wave edge search circuit uses a differential accumulation method to search for the pulse edge. To avoid the special case of all 1s or all 0s (i.e., data transitioning at time 0), the data from the first unit is inverted and used as the Nth unit's data. s +1 unit data; N s +1 data points are used to obtain N through front-to-back difference. s The differential results are processed through inter-pulse accumulation and non-coherent accumulation. The transition edge position is determined by peak detection. If the decision fails and the number of failures does not exceed L... s Next, L s To determine the maximum number of failed decisions, the circuit repeatedly performs edge-triggered searches. If the number of failures exceeds L... s If the decision is successful, return to step three to re-acquire the spread spectrum pseudocode phase. If the decision is successful, send out the result and calculate the target distance.

[0017] If the differential result shows a peak at the Xth unit, where X takes values ​​of 1, 2, ..., Ns, it indicates that the transition edge is located between the Xth and X+1th units. Combining this with the square wave transition edge position to resolve distance ambiguity, the unambiguous spread spectrum pseudocode phase is... Where T code For pseudocode period, The phase of the spread spectrum pseudocode with ambiguity obtained by the pseudocode acquisition circuit;

[0018] Based on the two-way distance measurement formula, the unambiguous target distance estimate is calculated.

[0019] Beneficial effects:

[0020] 1. This invention, through the waveform design of square wave modulated short-period pseudocode, not only retains the advantages of high processing efficiency and low computational resource consumption of short-period pseudocode, but also adjusts the detectable range of the target by designing the square wave period.

[0021] 2. The method of the present invention accumulates energy within the spread spectrum pseudocode period and searches for the square wave transition edge by differentiating the energy accumulation results within adjacent spread spectrum pseudocode periods. It resolves distance ambiguity while completing target detection and decision-making, and has high accuracy and reliability.

[0022] 3. The method of the present invention consumes few resources and has a short computation time. It can be effectively applied on small and resource-constrained platforms, and has practical application value and broad application prospects. Attached Figure Description

[0023] Figure 1 This is a flowchart of the method of the present invention.

[0024] Figure 2 This is a schematic diagram of the differential detection of the transition edge in this invention. Detailed Implementation

[0025] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0026] This invention proposes a fast range ambiguity resolution method based on square wave modulation of short-period direct sequence spread spectrum signals. According to the detection range requirements, a square wave period is designed, and by utilizing the phase relationship between the square wave and the direct sequence spread spectrum pseudocode, rapid range ambiguity resolution is achieved simultaneously with phase acquisition of the spread spectrum pseudocode.

[0027] The specific process of the method of the present invention is as follows: Figure 1 As shown, the specific implementation steps are as follows:

[0028] Step 1: Determine the square wave period based on the maximum unambiguous measurement distance.

[0029] Based on the maximum unambiguous measurement distance requirement of Rkm, the square wave period should not be less than Where c is the speed of light. For engineering purposes, rounding is convenient, so we consider using... As positive and negative square wave periods, the square wave period is 2Tms, and the maximum unambiguous measurement distance can reach 150T km.

[0030] Step 2: The transmitter transmits a direct sequence spread spectrum signal with square wave modulation.

[0031] Assume the transmitted signal is

[0032]

[0033] Where t k =k·t s (k = 0, 1, ..., K-1), t s Where K is the sampling time interval, K is the total number of sampling points, and P is the sampling point interval. t For the transmitted signal power, d(t) k ) represents the modulation data, S square (t k The signal is a square wave with a period of 2N. s One pseudocode period, and the positive and negative square wave widths are equal, PN(t) k f is a pseudocode without delay. I This is the intermediate frequency.

[0034] At the transmitting end, firstly, the data d(t) k The signal is multiplied with a pseudo-code to complete the spread spectrum, thereby improving confidentiality and anti-interference capabilities. Then it is multiplied with a square wave to increase the maximum unambiguous range, and finally modulated to the intermediate frequency f. I This generates the transmission signal.

[0035] Step 3: The receiver estimates the phase of the spread spectrum pseudocode within the period by using fast circular correlation.

[0036] Assume the received signal is

[0037]

[0038] In the formula, t k =k·t s (k = 0, 1, ..., K-1), t s Where K is the sampling time interval, K is the total number of sampling points, and P is the sampling point interval. s For the received signal power, d(t) k ) represents the modulation data, PN(t) k +τ) is a pseudocode with a delay of τ, f I For intermediate frequency, f d Let n(t) be the carrier Doppler frequency. k () represents noise.

[0039] The intermediate frequency signal is digitally orthogonally down-converted, L-point integrated and cleared, and circularly correlated to obtain the N-point I and Q signals:

[0040]

[0041]

[0042] In the formula, For local pseudocode latency, To estimate the Doppler frequency, L is the number of integration clearing points, i (i = 0, 1, ..., N-1) is the intermediate accumulation sequence number in the correlation process, n is the circular correlation result sequence number, and N is the total number of circular correlation result points, satisfying the relationship N = K / L.

[0043] Combining I(n) and Q(n) into complex form is:

[0044]

[0045] In the formula, The signal after integration and clearing. For the pseudocode after clearing the integral, t L =L·t s This is the time for clearing points.

[0046] Given the relevant theorems for circles:

[0047]

[0048] In the formula, X(K) and Y(K) are the Fourier transform results of x(i) and y(i) respectively, and * represents the conjugate operation. Comparing equation (5) and equation (6), we can... Seen as With PN(it) L The circumference is related to ).

[0049] If the effects of modulation data d(k) and noise n(k) are ignored, the results of quadrature downconversion will be affected. Perform an FFT and compare it with the local pseudocode PN(it) L Performing conjugate multiplication on the FFT of the given data, followed by IFFT, yields the fast circumferential correlation results. exist and Traversing within the search space, when and hour, The modulus of can achieve the maximum value, (·) N This represents a cyclic operation with a period of N. Therefore, it can be detected... The peak value is obtained, and after passing through the detection and decision logic, the spread spectrum pseudocode phase estimate is obtained.

[0050]

[0051] Where, n max for The index n value corresponding to the peak value.

[0052] Step 4: Despread using the phase estimation result of the spreading pseudocode, and accumulate energy within the spreading pseudocode period to obtain N. s This is the result of energy accumulation.

[0053] Based on the spreading code phase and Doppler frequency estimation results, the local pseudo-code waveform is regenerated and multiplied with the received pseudo-code to complete despreading. The integration clearing time is set to the pseudo-code period, and the coherent accumulation method is to first perform N operations within each square wave. s After the second integration and clearing, the square waves are accumulated again, finally yielding N. s This is the result of energy accumulation.

[0054] Step 5: The energy accumulation results within adjacent spread spectrum pseudocode periods are used to search for the square wave transition edge using a differential method to complete the target detection decision and distance estimation.

[0055] For N after energy accumulation s The square wave edge search circuit uses a differential accumulation method to search for the pulse edge. To avoid the special case of all 1s or all 0s (i.e., data transitioning at time 0), the data from the first unit is inverted and used as the Nth unit's data. s +1 unit data. N s +1 data points are used to obtain N through front-to-back difference. s The differential results are used. After inter-pulse accumulation and non-coherent accumulation, the transition edge position is obtained through peak detection. The implementation principle block diagram is shown below. Figure 2 As shown. If the judgment fails, and the number of failed judgments does not exceed L. s L s (To determine the maximum number of failed decisions), the circuit repeatedly performs edge-triggered searches. If the number of failures exceeds L... s If the decision is successful, return to step 3 to re-acquire the spread spectrum pseudocode phase. If the decision is successful, send out the result and calculate the target distance.

[0056] If the differential result shows a peak at the Xth unit (values ​​1, 2, ..., Ns), it indicates that the transition edge is located between the Xth and X+1th units. Combining this with the square wave transition edge position to resolve distance ambiguity, the unambiguous spread spectrum pseudocode phase is... Where T code For pseudocode period, The phase of the spread spectrum pseudocode with ambiguity is obtained by the pseudocode acquisition circuit.

[0057] Based on the two-way ranging formula, the unambiguous target distance estimate can be calculated as follows:

[0058]

[0059] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals used in radar measurement, characterized in that, Includes the following steps: Step 1: Design the square wave period based on the maximum unambiguous measurement distance requirement; Step 2: The transmitting end transmits a direct sequence spread spectrum signal with square wave modulation; Step 3: The receiver estimates the phase of the spread spectrum pseudocode within the period using fast circular correlation. Assume the received signal is In the formula, , , The sampling time interval, This represents the total number of sampling points. To receive signal power, For modulated data, For those with delay pseudocode, The intermediate frequency, For carrier Doppler frequency, For noise; The intermediate frequency signal is digitally orthogonally down-converted, L-point integrated and cleared, and circularly correlated to obtain the N-point I and Q signals: In the formula, For local pseudocode latency, To estimate the Doppler frequency, Clear points for points. To accumulate sequence numbers in the relevant processes. , This is the sequence number of the circumferential correlation results. Let be the total number of points in the circumferential correlation results, and satisfy the relation... ; Will and Combined into complex form In the formula, The signal after integration and clearing. This is the pseudocode after clearing the points. This refers to the time for clearing points. Given the relevant theorems for circles: In the formula, , They are , The Fourier transform result, * represents the conjugate operation; Will Seen as and Circumferential correlation; If modulation data is ignored and noise The impact on orthogonal downconversion results Perform FFT and compare with local pseudocode Performing conjugate multiplication on the FFT and then performing IFFT yields the fast circumferential correlation results. ;exist and Traversing within the search space, when and hour, The modulus can achieve the maximum value. Indicates A cyclical operation; through detection The peak value is obtained, and after passing through the detection and decision logic, the spread spectrum pseudocode phase estimate is obtained. in, for The index n value corresponding to the peak value; Step 4: Despread using the phase estimation result of the spreading pseudocode, and accumulate energy within the spreading pseudocode period to obtain... The result of energy accumulation; Step 5: The energy accumulation results within adjacent spread spectrum pseudocode periods are used to search for the square wave transition edge using a differential method to complete the target detection decision and distance estimation.

2. The method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals for measuring radar as described in claim 1, characterized in that, according to The maximum unambiguous measurement distance requirement is that the square wave period should not be less than [a certain value]. in The speed of light; For ease of rounding in engineering, it is recommended to use... As the period of positive and negative square waves The period of the square wave is The maximum unambiguous measurement distance can reach: .

3. The method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals for radar measurement as described in claim 1, characterized in that, At the transmitting end, the modulated data is first multiplied by the pseudo-code to complete the spread spectrum, then multiplied by the square wave to increase the maximum unambiguous distance, and finally modulated to the intermediate frequency. This generates a transmission signal.

4. The method for fast range ambiguity resolution of short-period direct-sequence spread spectrum signals for radar measurement as described in claim 1, characterized in that, After energy accumulation The square wave edge search circuit uses a differential accumulation method to search for the pulse edge. To avoid the special case of all 1s or all 0s (i.e., data transitioning at time 0), the data from the first unit is inverted and used as the second unit's data. Cell data; The data were obtained by difference between the preceding and following data. The differential results are processed through inter-pulse accumulation and non-coherent accumulation. The transition edge position is determined by peak detection. If the decision fails, and the number of failures does not exceed a certain limit... Second-rate, To determine the maximum number of failed decisions, the circuit repeatedly performs edge-triggered searches. If the number of failures exceeds this limit... If the decision is successful, return to step three to re-acquire the spread spectrum pseudocode phase. If the decision is successful, send out the result and calculate the target distance. If the result after difference is displayed in the th... A peak value appears at each unit. The values ​​are 1, 2, ... Ns This indicates that the transition edge is at the 1st... Unit and the Between units, combining the square wave transition along the position to resolve distance ambiguity, the phase of the unambiguous spreading pseudocode is: ,in For pseudocode period, The phase of the spread spectrum pseudocode with ambiguity obtained by the pseudocode acquisition circuit; Based on the two-way distance measurement formula, the unambiguous target distance estimate is calculated.

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